PROSPECTS FOR LEARNING TECHNOLOGY

In this chapter, we look at the issues raised in the preceding chapters and attempt to relate them to one another in a coherent view of learning technology. On the one hand, we will be looking once again at some provocative ideas that were raised in their initial context and see how they fit in with the rest. And on the other hand, we will seek to merge the commonality within these ideas into a synthesis that summarizes the broad perspective presented. This will lead us to an assessment of what issues remain pending. It will also let us assess how the theoretical view that is proposed fares as a whole.

I have been concerned in this book with four different perspectives on learning technology. The first two concern the future portrait of learning technology: the societal context in which it will develop, and the growing intelligence it will embody in various forms. The last two do not specifically concern the future, but rather the perennial issue of learning, and how to foster learning through the design of materials structured within learning environments. We must see how these four concerns fit together into an overall perspective on learning technology.

THE FUTURE OF LEARNING

The future is of course difficult to predict. We are constantly reminded of this by looking around us and seeing all those personal computers being used for a wealth of intellectual activities. The personal computer came and imposed itself without generally having been predicted as a strong force in the computing world. Nevertheless, it is natural to ask ourselves what intellectual technology is just around the corner that will pervade the 21st century, and that we are not yet very aware of? In reality though, we will simply have to wait and see.

In the meantime, we extrapolate from our current situation into a future world that is heavily computer-centered and in which there is a very intense flow of information in electronic form.

Now, one of the basic theses put forth here is the view that the increased availability of information in compelling forms will practically by itself lead to increased learning. The effin factor is invoked to explain this phenomenon. How realistic is this thesis? Why would more information lead to more learning?

The reason to be optimistic about the thesis is that much of learning rests on our natural propensity to be curious. Eliminating the barriers to the flowering of that curiosity will naturally lead to increased learning. Those current barriers are the unavailability of information at the time it is needed, and the regimented and fractionated curricula encountered in many schooling contexts. Learning technology will help on both fronts.

The magic of learning technology is not hard to find. It lies in the ease of access that is provided by the electronic nature of the medium. Our interests in matters of knowledge are oftentimes fickle. Our great curiosity makes us jump from one thing to another, easily, and constantly. We are in constant interaction with the world around us, our focus going here and there, depending on the situational attractions exerted upon us at the time. All learning technology does is make pertinent information part of that situation. The effin factor ensures that, given the opportunity, curiosity will lead to searching out information of interest. Learning technology simply gives information a chance to exert its own measure of attraction and capture a person's interest.

Thus, natural curiosity and availability of the pertinent information combine to create a situation that is very propitious for learning. That does not mean that learning will forever take over a person's full interest. There are other things in life as well as learning, and these will continue to request a person's attention. But, at least, when curiosity is piqued, there will a chance for it to lead to something. The climate will be there for learning to occur.

The lack-luster climate of our current schooling forms the second barrier to the natural flowering of curiosity. The ringing of the bell at the end of a class period, followed by the rushing out of the students, symbolizes the artificiality of the contrived learning environment that schooling has led to. It is basically the organizational features of schooling, its handling of masses of students, that have led to the current improper climate for learning that is found time and again in our classrooms. It is a courageous and inspired teacher that can light up the students' interest despite the unpromising environment.

The progressive education movement of yesteryear, now being renewed in the cognitive apprenticeship approach that stresses situated learning, saw the difficulties of schooling, but was unable to establish itself as an effective countering force to the institutionalization of large-scale management in schooling.

The philosophy of situated learning is one that seeks to interest the person in the learning enterprise by focusing on tasks that are intrinsically useful to the learner and by constantly bringing that usefulness to the fore. The context for learning is what makes it meaningful, and hence interesting. Learning becomes motivated and rewarding. A slightly different philosophy than that underlying learning technology is at play here, although the overlap between the two is substantial.

Situated learning interests through its usefulness, whereas learning technology is meant to interest through the interesting-ness of the learning materials, irrespective of usefulness. We are dealing with the difference between motivated curiosity and epistemic curiosity, knowledge for the sake of being able to do something and knowledge for its own sake. Both, of course, can work together to the benefit of learning.

Now, an interesting issue presents itself in this context. Just how pure and unmotivated is knowledge for its own sake? Can epistemic curiosity be divorced from a general utilitarian context that would seem to inevitably situate learning? In other words, do people really pursue things that don't really matter to them in some way? I believe the answer to be yes.

The reason for this answer lies in the fickleness I spoke of earlier, for we do not fully control our interests. An event happens that arouses our curiosity, and there we go, off on an avenue of exploration to satisfy our curiosity. Epistemic curiosity is one that is based on a need for closure, a need for being satisfied with what we know.

Of course, I never do know what my exploration of the geography of Russia will lead to, for instance, nor how it might one day become useful, if at all. I do know, though, that knowledge is useful in a general manner, even if it might only be to appear knowledgeable. In that sense, epistemic curiosity is motivated by a general need to accumulate knowledge and develop skill. It is situated, although very generally so.

What is not situated is the school-based learning that is artificially organized, lacking in immediately perceived usefulness, and hence in personal meaning, as well as very often being un-interesting. The situated learning approach seeks to reform schooling within the current schooling structure, and hopefully, it will succeed.

Learning technology as presented in this book has a very different approach to enhancing learning. Rather than being a teacher-based approach, as situated learning is, it is a tool-based approach. The learning tools of the future will have their impact out of school even more that in school. Indeed, the whole of schooling, very directly because of learning technology, will be transformed, as related in the learning scenario I presented in the early part of the book. The school, as a place to park the kids, and as 'the' place where learning supposedly takes place, will give way to a more fruitful conception of schooling. The place for learning most things, but certainly not all, will be in interaction with a learning tool. Technology will play an ever increasing role in learning.

The economic factor of course enters the picture of the future of learning. Fascinating learning tools will be costly to develop and to refine on a continuing basis, as well as to make available to those who want them. This does not imply that learning technology will be inordinately expensive; given its electronic basis, it may well turn out to be inexpensive in relative terms. What is implied is simply that you get what you pay for. Just as poor funding of education leads to poor schooling, a poor funding of learning will eventually lead to a poor learning technology. Education and learning are no different than other facets of society in this respect.

Given the emphasis on technology as a medium for learning and given curiosity as a basis for learning, will our children be oriented to learning? Society will be no different then than now in its orientation to personal growth and success. Some parents will continue to push and encourage their children, and others won't. Some children may well not take advantage of the learning tools around them and waste their time instead. But on the whole, that is not likely to occur, for even children eventually get bored and seek out ways of amusing themselves. In as much as learning technology can be made fascinating, and that is the purpose of learning environment design, then a healthy orientation to learning should be no problem for children.

As for those intrinsically less interesting things that must be learned one way or another (the multiplication table and other such realities), the challenge of games that develop such skills in a painless and surreptitious manner will be brought to bear on the task of ensuring mastery in these areas. Just as situated learning seeks its motivation in relevance, learning technology seeks it in epistemic curiosity, and where that is intrinsically lacking (as in '8 x 9 = ?'), it seeks it in the very real source of excitement that gaming provides. This reliance on extrinsic motivation may seem unfortunate to some, but natural curiosity does have its limits. Relying on another source of motivation should not be shunned for skill areas that cannot be made interesting in themselves. What should be frowned upon, however, is the use of secondary motivation to prop up instruction that has not been properly designed to bring out the child's natural curiosity in the first place. The whole purpose of LED is to do away with non-intrinsic motivation where that is at all possible.

A number of further ideas that may seem provocative were put forth regarding the future of learning. One was that a separation will eventually occur between learning and the certification that currently occurs through testing. Another, that learning needs may well diminish as intelligent systems take over more of the symbolic processing that we must now do ourselves. Yet another, that disciplines will come to compete for our attention in terms of learning. All of these ideas build upon the more fundamental assumption that learning will leave school and become more and more a life-long venture that becomes more intrinsic to our pattern of living. Today, we dip in and out of schooling in a life-long pattern of educational upgrade. Tomorrow, we will dip in and out of learning, schooling taking on an altogether different character than it has today.

How quickly these transformations will occur is difficult to say. They all rely on the development of a sophisticated learning technology. It is that technology that will drive the changes and lead to a different social structure for learning.

Is learning technology in danger of being seen as a futuristic panacea? Certainly it is, and there is no reason why it shouldn't be. Learning technology is not the answer for our current schooling problems. It just isn't there yet. Nor is it something we need particularly to sacrifice for in order to bring it about in a rapid manner. Learning technology will develop in its own good time and under its own steam. Like science, you simply cannot stop it, nor can you make it happen the way you think it must happen.

INTELLIGENCES AROUND US

The future of learning is bound up with intelligence in systems around us. Electronics provide two capabilities that learning environments will capitalize upon: reproducibility and intelligence. Reproducibility is the ability to establish realistic environments that enable people to vicariously experience the world. It is, for instance, graphically representing what Tokyo looks like, or showing what one would see if standing on Mars.

Reproducibility enables learning to move away from the overly abstract and back to a more genuine apprehension of the world around us. The experiential, sensuous, and iconic can be used to advantage to bolster learning, all the more so in a context that values the interesting-ness of domains of knowledge. And it is the electronic medium that will provide this feature of reproducibility to the extent that curiosity will require it.

It is the feature of intelligence, though, that will be of greatest importance in learning technology. Intelligence will enable systems to take on an active role in facilitating learning, a role that is currently performed by people. Teachers are the principal role-players in instruction currently, but good teachers are limited as a group, as well as being costly. These constraints can be eliminated through the growth of intelligence in tutoring systems.

Is this an over-optimistic scenario, given the relatively poor performance, as of yet, of artificial intelligence as a practical technology? The promise of artificial intelligence is still with us, and its poor performance to date is merely a relative one. So the expectation of intelligences around us in the next century is not unrealistic if we accept artificial intelligence for what it is.

We still tend to overreact to the notion that intelligence can be artificial. If we take intelligence to merely be complex symbol manipulation that is goal-oriented, then it is all very feasible. If we insist on artificial intelligence being a replication of human intellectual activity, with the full richness that is provided by our sensuous interaction with the world and our animalistic drives, then we are overreaching ourselves in demanding too much. It is sometimes fun to quibble about what it means for us to be intelligent, or for computers to be 'artificially intelligent', or not 'really' intelligent, but we must not forget that we are also tool-builders. If we can design practical tools that assist us in our intellectual tasks, be they tools for adding numbers or for discovering new mathematics, then the philosophical issues of AI are merely a sideline, something for discussion over coffee.

It is interesting how we used to believe, a century and a half ago, that we were biologically special, until the truth of evolution was finally made plain. Nowadays, many believe that we are intellectually special, and soon perhaps, scientific history will have occasion to repeat itself.

Intelligence is the application of knowledge to particular tasks, be that knowledge of specific details of a domain or of intellectual procedures for furthering a goal. Knowledge itself is encapsulated information, structured through the semantically logical constraints that we perceive and act with. Even our artifacts encapsulate knowledge. Imagine a native of a primitive region finding a metal pot left by an explorer. Its function as a container for water would soon be put to good use. The hollowness of the pot and its general sturdiness both fit in with the requirements for keeping water. Not very good for keeping firewood in, though. Our inner world is built upon these semantic constraints, as well as our built environment.

The knowledge we possess as individuals, in our minds, is simply structured information that can be used by cognitive processes for attaining our goals. We have lots of it, for we have continued to accumulate and enrich it ever since childhood. And that is what is missing in computers. They lack the gobs of information we have, what has been called common sense knowledge. But if we recognize that the nature of the difference is merely a quantitative one, and not a qualitative one, then there is no reason to not expect intelligences to grow around us. They will do so eventually, in their own good time.

INTELLIGENT ASSISTANCE FOR LEARNING

Learning is an individual activity: it has to be done by the individual person. Teaching can assist learning, but it cannot accomplish anything on its own, without a commitment to learn. All tutoring systems simply structure the learning context so as to make it appropriate for learning. The parent that fills the child's room with colorful books is doing just that, as is the computer tutor that gives the child feedback and provides more problems at the appropriate level of difficulty. Teaching is a motivated attempt to influence learning, irrespective of how directive it is.

As an individual activity, learning happens all the time, for the basis of learning is the interaction of the individual with information in the surrounding environment. But the information has to fit: the appropriate information has to be present at the right time so the learner can make sense out of it and incorporate it into his or her cognitive structure. That is why teaching is essentially a process of deciding what the learner's cognitive needs are, and ensuring that the proper information is there to interact with at the specific time of need.

What to provide and how to provide it are the two core decisions involved in teaching. The first is a curricular decision, but as learning technology makes information more and more available, decisions about what is interesting to learn will tend to conflict with outside influences. The learner perspective may well not jibe with the teaching perspective. The issue is one of control and it has remained an issue throughout the history of education. Learning technology may simply exacerbate the issue, but cannot deal with it, given its political nature.

Learning must not be seen, however, as simply some wanton exploration of information in a learning environment. Part of the influence in teaching, part of its curricular decision-making, is the guidance provided regarding the goals that are appropriate for the learner to pursue. This is the cognitive tasking that is central to teaching, and which applies both broadly (what topics to explore) and specifically (what the best course of action is right now).

Assisting learning, therefore, is always a question of deciding specifically what information the learner now needs, in order to proceed most efficiently. That may be task information, or feedback regarding some attempt at using a skill, or a piece of detailed information to fill out a picture of some topic. The teacher, or teaching system, assesses the learner's needs and reacts appropriately. The issue of who controls the interaction is left open. In fact, the learner and teacher each constitute an active system that pokes the other and reacts to the other's own poking.

While the issue of control of the interaction involved in learning remains open, it is central to the forms of intelligent system that make up the field of learning technology.

EMERGING FORMS

Learning occurs through a goal-directed interaction between learner and information environment. It is this environment that learning systems provide in rich and adaptive forms. The poking that the learner engages in can be more or less goal-directed or open, just as the cognitive tasking that the system undertakes can be more or less focused or broad. These factors determine control of the interaction and play a large role in distinguishing particular learning technologies.

All systems designed as learning technologies enter into cognitive tasking, be it broad or narrow. Hypermedia systems, for instance, involve very broad tasking, their goal being to engage the learner's interest, while generally leaving him or her the decision as to the specific direction that interest will take. The cognitive task a hypermedia system gives the learner is simply to explore the information in the system. Even an intelligent hypermedia system, while it might use its knowledge of the learner to filter the information to suggest at a given point in time, still leaves the specific goal orientation to the learner him- or herself. We are dealing here with very broad cognitive tasking.

Intelligent tutors, on the other hand, generally involve much more focused cognitive tasking. They are much less passive in control, and tend to lead the learner's train of thought towards correct mental modeling of the information being learned. After putting the learner in a situation in which some form of performance is expected, tutors guide the learner towards a correct form of performance. The tutors provide the goal orientation for the interaction. Despite the appearance of learner-control provided by the flexibility and adaptability of some of these systems, the tutors closely monitor learner performance and adapt to that performance.

Are we to think, then, that control can be given to the learner when handling information representations, but should remain with the system when dealing with skills? This is probably the right conclusion to draw, in a very general sense. The reason for generality here is that many tasks are not simply information or skill, but involve some combination of both.

Information of the kind found in hypermedia systems involves structured representations that must be meaningful if they are to be pursued, and that must therefore appeal to the learner's understanding. The learner is generally the best judge of his or her own understanding, and hence it make more sense for control to remain with the learner. Skill, on the other hand, and especially the high automatization of skill, is less meaningful and may often require simple practice to provide the repetition that will strengthen the associations in one's mind. Here, the learner is much more willing to hand over control to a system that can monitor performance and provide the proper level of challenge for developing the skills in question.

The context of the task essentially distinguishes the role that different systems can play. If a task has little intrinsic interest, then gaming can be taken advantage of to keep the learner on task. But if the task is inherently interesting, then gaming is not necessary, and tutors or hypermedia environments can be designed for learning.

Guardian angels form a special case, for they are not systems from which to learn, but rather systems that may provide guidance regarding the proper utilization of resources. While they know their learner well, they do not possess domains of knowledge. Their role is thus different from that of the learning technologies themselves.

The forms of intelligent system portrayed here must be seen in the current context. They are in that sense representative of eventual learning technologies rather then being comprehensive. Other novel forms of learning technology are sure to emerge as the electronic technologies themselves continue to evolve over the years. Forecasting the future state of learning technologies can only be partly successful in this sense. What even a partly plausible forecast provides, however, is indications of the general possibilities that lie ahead.

DESIGNING LEARNING TECHNOLOGIES

A new approach called Learning Environment Design (LED) was proposed to replace the more traditional design technology known as ISD. The latter is overly geared to the attainment of learning results at the expense of learner interest. The consequence of this approach is that those students who are strongly motivated to succeed do succeed in learning what is expected of them. Therein lies the power of ISD, but it is hardly an ideal situation.

The crucial difference between ISD and LED lies in the goal-orientation of the eventual learning materials: strong in ISD instructional materials, weak in LED learning environments. Instructional materials, and instruction generally, are motivated by having a specific effect on the learner population. They direct the learner towards achievement. Learning environments, however, give more control of the interaction to the learner. ISD-based instruction is aimed at knowledge communication in the strict sense, whereas LED-based learning favors knowledge exploration, even though in the global sense, there is invariably an intent to influence, in a general manner, the eventual knowledge of a learner population.

The interesting aspect here is that, in traditional instruction, the learner actually hands over control to the instructional system, in effect saying 'I don't know how to go about it, nor even exactly what I need, so you do it. Take charge and ensure that I learn what I have to.' While this is of course an exaggeration of any real situation, it brings out the orientation that all teaching involves. The drawback of the ISD approach is that it easily alienates the interest of the learner, for any teacher can often only guess at exactly what the learner's needs and interests are at a given moment, and certainly has trouble doing that for a group of learners. The teacher-led interaction may be on the mark some of the time, but it will likely be off the mark a good deal of the time, too. It is from this deficiency that the often strongly-felt need in instructional systems for external forms of motivation comes about. Just keeping the learners involved is often a whole task in itself.

The point of LED is to develop interesting materials for learning. While ISD is constrained by its goal to achieve some particular learning results, and hence constrained by the very content of instruction, LED is freer with respect to content, its main constraint being the challenge of attractiveness. Indeed, since the learner her- or himself leads the learning interaction, the materials have to provide attraction value, especially when ease of access will ensure that topics compete with each other for the learner's attention and allegiance. The provocation of curiosity becomes an important challenge for learning design, with variability, surprise, uncertainty and incongruity being facets of information with which to structure learning materials that will pull the learner into exploration and keep involvement at a high level.

Can it be done? Or is this merely the holy grail of teaching that is being described as a panacea for our global learning ills? The thesis put forth in this book is that it will be done, it will come about whether we believe it or not. This revolution will be technology-driven, so there is not even a need to push this point of view in political terms.

How it will be done is through the continuing emergence of learning technologies in various forms, such as those described in this book. Reproducibility and intelligence will combine in such learning environments as games, tutors and artificial realities to cognitively task the learner, thus arousing learner interest, aa well as to provide the necessary information to enable the building of knowledge and skill. The core process involved in the operation of all learning technologies is simulation. This in fact structures the information, and through intelligence, enables the reactivity and interactivity that provide the appropriate context for learning.

Two issues loom in the background of learning design: the issue of abstraction, and that of need context. Reproducibility is the potential to provide the world to the learner without the real constraints of the actual world. It emphasizes the sensuous and enactive interaction with information and provides much of the interest factor that is so important for learning. But the world of abstraction is also an important sector of our world, the most important one in many respects. And so what we need to see developing in LED is a way to interweave the different levels of experiencing the world, ensuring that there is constant travel back and forth between the sensuous and the abstract. The great tragedy of much of instruction of a formal kind is the lack of the sensuous base, and a sole reliance on the power of the abstract description to nurture learning. The power of abstraction lies in the logic that underlies it, but that in itself is generally insufficient to carry interest in learning.

The second issue that the design of learning must confront is the one of need. Whether a need is immediate (and that is where interest can also be highest), or whether the need is more remote, will affect the whole tone of the learning interaction. The future will strongly impact this issue. On the one hand, the future of learning technology will empower people to seek and obtain the information they need as they need it, thus alleviating some of the difficulty experienced in this area. On the other hand, in many instances, remote needs can be made more immediate through the very potential of simulation as a basis for learning technology. The remote activity of removing a patient's liver, for instance, can be experienced by the budding medical student, or the use of trigonometry in designing an amphitheater can be made evident by that very design activity simulated in some artificial reality. There will remain, of course, the need for remote and yet unsituated learning needs, but these will be fewer, and they can be tackled through such artifactual learning environments as games.

Before leaving this topic of learning environments supported by a sophisticated technology, I want to make clear that the vision that is emerging is definitely not one of anti-social learners working at individual computers and interacting with intelligent but artificial structures, rather than with other people. On the contrary, there will quite likely be more interaction than currently, for the very sensible reason that learners will want to share with others the excitement generated through powerful learning experiences. Our social instincts for sharing interesting events, and learning should definitely fall into that category, are usually stunted only by the rigidity of organization required to handle groups confronted with un-interesting learning tasks. The future will probably lead us to see diads of learners jointly exploring some topic of fascination to both partners, or small groups of learners gazing at what one of them is manipulating on a large screen in front of them. Let it not be thought that sophisticated learning technology breeds a style of interaction that is inappropriate to the social animals that we are.

PINPOINTING LEARNING

Underlying learning technology is the process of learning itself, for the whole purpose of learning technology is to make learning possible. The requirements for learning are simple, and yet difficult to arrange. All that learning requires is the right piece of information at the right time, and that is what is so difficult to obtain or to provide, at least currently. But it is also why information technology is bound to revolutionize practical learning by removing the current barriers to accessibility.

Accessibility makes learning possible by providing the right information at the right time. It also encourages learning through the effin factor: ease of access makes the process all the more painless and thus encourages interaction with information.

Given accessibility, just how simple is learning? The regularities and irregularities of the world provide the basis on which learning takes place. The regularities lead to abstractions, which in turn combine to form complex structures that model the world for us. Learning itself is simply the natural recording of these regularities, at whatever level of abstraction they occur. And when the regularities are not as regular as we would want them to be, then we force them to occur through the process that we call rehearsal. This use of regularities forms the associative basis of learning.

But given that people have a capacity for thought, they use this power to by-pass the need for rote learning. They in effect use the power of thought to put coherence to work, thereby following through the logical implications of a situation and thus reducing its arbitrariness. This structural aspect of learning invokes the semantic logic which was the result of prior learning and which now provides the required framework for processing information in such a way that it is assimilatable into one's current cognitive structure.

This inferential approach to learning is always sought by the learner since it greatly simplifies the task of learning. The reason for this is that the person's striving for meaning is also active during recall, and indeed logic here plays a most important role in reconstructing the knowledge that is now needed. Thus, the power of inference in both initial learning and the eventual reconstruction of information obviates the need for repetition in assimilating the world around us.

Our understanding of the world is a highly inferential and generative process that frames our total interaction with it. It is when understanding is not possible, that is when the information is fully arbitrary in itself, that rehearsal must be engaged in to learn the information. Another such situation is when the proper information is not available to the learner, and hence understanding is not reached; at times, the learner will then artificially learn by rote even though the information is potentially meaningful. Hardly a desirable situation, however.Our search for understanding, and our orientation to learning generally, derives from our natural curiosity. Epistemic curiosity fulfills the need we have for closure in an open-ended situation, and a more basic need for predictive regularity in our grasp of the world. All of this has been useful to us in an evolutionary sense, and that is surely why learning is the way it is.

Curiosity is the basis for our interaction with the world. Philosophers generally have made much of the subject-object relationship in examining epistemology as a facet of the learning issue. Jean Piaget, in particular, has focused on the interaction to explain learning in terms of a cognitive equilibration attained from assimilatory and accomodatory processes.

I prefer myself to look at the relationship in terms of an information transaction. The learner reaches out for information to fill a curiosity need in what I have called the process of curiosing. Reciprocally, the information encountered stimulates a constant attempt at consolidation within the learner's cognitive structure. There is thus a constant interplay between seeking out new information and managing what one finds. While the outgoing search may be more or less directed, the information uncovered may prove to be not only more or less relevant, but also more or less coherent with what one already knows. This in turn engages the interplay between repetition and structure. At a very general level then, learning is described in terms of two core cognitive activities: curiosing and consolidation.

The role of learning environments must be responsive to these requirements of learning; they must be designed to support both curiosing and consolidation. The beauty of the situation, though, is that it all boils down to obtaining the right information at the right time. Hence, the promise of the future, as the age of information technology.

A THEORY FOR LEARNING TECHNOLOGY

Learning technology rests on two underlying theories: a theory of learning and a theory of design for the building of learning environments. The view of learning presented in this book is built around the role of coherence in cognitive processing, so it could be called a coherence theory of learning. The proposal for a new approach to design, because of its emphasis on the interesting-ness of learning materials, is called learning environment design, with LED as its acronym.

The coherence theory of learning and LED combine to create a view of learning technology that is futuristic, in the sense that we are not yet there, but very plausible given the evolution of information technology that we are witnessing. At the core of learning technology is an appreciation for the interaction between learner and information, what could be called a transaction theory of learning technology.

These are the three theories that have been sketched in this book. They are interrelated and they are prospective in character. Indeed, they concern learning in an age of information availability, an age which is not too far away.

We are dealing here with processes of transformation as the age of information takes hold and molds society and ourselves as individuals to the new possibilities that arise out of it. Change is predicted in how we go about learning, in what we learn, and perhaps even in how we learn. Changes are certainly predicted in how we design learning materials, and more generally, in how we interact with technology and the institutional structures around us.

The design theory that will take root is one that brings in interest as a key factor in design, with the aim of minimizing non-intrinsic forms of motivation in the realm of learning. That human curiosity can be taken advantage of revolutionizes the way we think about learning as a practical human activity. Schooling as an institution can be radically transformed by LED, although it is really the simple availability of information that transforms, through the effin factor, our relationship with the world of information around us. How we go about learning will be irrevocably affected, as well as what we go about learning.

As the technology evolves to provide ever more reproducibility and intelligence, the nature of how we process information may well change. This does not mean that core learning processes, evolved over the millennia, will suddenly change. Rather, it simply implies that, as learning becomes more immediate, more motivated, more meaningful, coherence will have an ever greater chance of playing a central role in learning. Incomprehensions should be removed more quickly and cleanly than is the case currently. While human memory will never be anything but associative, the learner's constant striving for coherence will be easier and should remove some of our current reliance on rehearsal as a mechanism of learning; without, however, eliminating it altogether, since our world is not only a logical one, but also an arbitrary one as well.

The coherence theory of learning views learning as a single phenomenon, modulated by the degree of coherence to be found in a given situation. The result of learning is an associative structure in memory which is built up with more or less repetition, depending on the coherence, or lack of it, that is available to the learner. Meaningful and rote learning are but two facets of the same phenomenon.

What a transactional view of learning technology brings out is the importance of the right information at the right time as a basis for learning. Curiosity fulfilled carries with it a process of knowledge consolidation that equals learning. Learning technology will provide the means for satisfying that curiosity. I can't help but believe that the prospects for learning are just tremendous, given the coming technology.

The views of learning, of design, and of technology that I have presented in this book appear to me to be not only coherent, but plausible as well. But who am I to say? The level of discussion that I have engaged is a very general one, one which is certainly open to many different possibilities, open to various theoretical views. I have deliberately shunned grounding this theoretical exploration in current views of the phenomena discussed, both because these views are generally too narrowly situated in our current perspective, and because such grounding often serves as a foil for the critical examination of the ideas themselves, on their own merits. The theoretical discussion this book represents is thus an invitation to further reflect upon and represent the emerging field of learning technology.

Many ideas presented here have only been informally specified and continue to lack precision. That is the result of an adventurous approach to theory, rather than the cautious, but alas more conservative, one often advocated in academic circles. Many issues thus remain open for further exploration, and my hope is that learning technology, as a set of considerations for the near future, will take off as a field of study that not only promises much, but also creatively designs the future.