Adaptive Tutoring:

Adaptive tutoring is possibly the most commonly intended meaning when authors use the term "adaptive instruction." However, even within this meaning of the term adaptive, it is often used to describe at least two very different instructional service strategies: homeostatic and truly adaptive. To appreciate these differences, one needs to understand a bit about general systems theory, cybernetics, and especially adaptive control systems. General systems theory defines both a philosophical and practical approach to the world as being composed of hierarchically arranged systems which are especially defined by unique organizational and operational/process characteristics. Cybernetics is a discipline which stresses the role of feedback in the control and maintenance of a systems structure and/or operational dynamics. It helps to differentiate, for example, between homeostatic systems vs truly adaptive control systems.

Homeostatic characteristics are incorporated into most modern "adaptive" instructional software systems. That is, most adaptive instruction systems are designed to "sense" the current knowledge level of the learner--ususally through the application of an automatic knowledge generation engine-- and to "adjust" services to meet a singular and pre-established goal of accomplishment. It is this ability to adjust services that prompts most designers to refer to this instructional design element as "adaptive." That is, the system is designed to adapt itself to help the student meet a given instructional goal that has been pre-determined by the instructional designer, much like an air-conditioner strives to cool a room to the pre-determined setting established by someone inhabiting the building.

Unfortunately, this is a rather weak use of the term "adaptive." It certainly is not a term that cybernetic and systems researchers would use to describe the dynamic stability of other homeostatic systems. These researchers reserve the term "adaptive" to quite a different type of control system; that is, one that has the capability of adjusting its own "set point" to meet long-term needs of remaining intact. Such systems normally incorporate not only the previously mentioned metaphorical capabilities of "sensing," "comparing," and "controlling," but also that of "learning" (another word for "adapting").

A closer consideration of how biological systems work will perhaps illustrate this distinction more clearly. In human weight control problems, an individual ideally eats to maintain a given energy requirement of his/her body. If the individual goes on a diet, it typically isn't long before the individual finds that his or her weight gradually returns to the weight they were before starting the diet. This diet-induced artificial drop in normal weight gradually has the effect of controlling eating intakes sufficient to return the body to a prior "set-point." This is homeostatic.

However, when familiar and trusted food sources disappear, the first true adaptation actually arises through the individual's ability to adjust his/her habits of visiting singular and formerly trusted resource areas for finding food. In such cases we, as well as all other types of animals, begin searching for alternative food sources, which is one form of adaptation--behavioral adaptation. But in times of extreme and sustained food-source disruptions, the body calls upon a more fundamental biological adaptive mechanism by resetting its "need" for large amounts of food altogether. This also is adaptation.

Our human weight-loss diet example will help illustrate these alternative forms of adaptation. Researchers have discovered that, in fact, extraordinary efforts to change behavioral life-style patterns (such as increasing exercise) and fundamental food consumption habits (such as reducing our reliance on high-fat foods) can bring about a change in hypothalamic set-points (as can surgical extirpation of those responsible areas of the hypothalamus in animal experiments--which is how we know about the phenomenon in the first place). This means that with specially designed environmental contingency management programs, we can bring about behavioral adaptations which, in turn, influence the biological energy system to adapt by altering its actual set point. Thus the human energy system is not only homeostatic, but capable of being truly adaptive as well--which is highly functional for ultimate species survival in times of prolonged and severe food shortages. Under such conditions, set points are being changed to accommodate available resources and contingencies when the maintenance of old dynamic stabilities are no longer feasible. Darwin even saw such mechanics of adaptation at work at the level of genetics and the evolutionary transformation of the structural and functional capacities and characteristics of entire species.

Applying the above distinctions and definitions to instructional software systems requires that we become aware of the limitations of most pre-established educational goals that are built into those systems. Perhaps what we really need to build into such educational systems is not only the ability to adaptively teach a student the content of the moment, but also the ability of the system to teach higher-level skills that actually transform the learner in fundamental ways, such as developing reading, listening, and viewing comprehension; or the ability to create self-reflective concept maps and semantic networks of understanding; or even advanced problem-solving abilities.

Such a system should not only adjust to the momentary (homeostatic) needs of the learner, but should also recognize when that learner is becoming more "adept" at learning the material and should respond by challenging the learner to more advanced forms or levels of learning. That is, adaptive instructional systems should not only improve a student's knowledge base, but also his/her learning skills. To do so requires that such a system be capable of shifting its educational goals as well as its services for helping a student accomplish those goals.

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