Table of contents

Abstract

What is a hypermedia system.

Let's suppose, for example, that the field of knowledge is biological taxonomy. Presumably, the way in which this knowledge is organized in the mind of somebody who knows biological taxonomy is some sort of hierachical tree-structure relating species and genera (KS) . If one has to communicate this field in the form of a textbook, one will have to map this hierarchical tree- structure into a linear succession of chapters (CS). In doing so he will be forced to choose, for example, whether to "scan" the tree (so to speak) at each level of nodes and, hence talk first about all classes, then all orders, then all families, then all genera, then all species, or to scan it along each branch and talk about, for example, the order of primates, the familiy of lemurs, the genus Lemur and the species Ring-tailed lemur, and so on. The learner, on the other hand, will have to start from this linear succession of chapters (CS) and try to reconstruct from it the hierarchical tree-structure (KS). Since KS is, for any knowledge field, given, the only way to simplify the mapping operation is to try to change CS in such a way that it is more similar, or, if possible, identical (isomorphic) to KS. In this way the communicative structure would become "transparent" with respect to the knowledge field. Obviously, this cannot be done through the textual medium which has only a pan-linear structure. Let's give some concrete, though very simple, examples of how this change can be effected and, at the same time, convey an intuitive appreciation of the remarkable difference it causes on the cognitive process of understanding. Let's suppose that the "knowledge field" is a very simple one, like variation of a quantity (say, output production) through time (say, successive years), than one can compare the difference between communicating this information through: (a) a textual description; (b) a line graph.

(a) "In 1983 production was 420 units and it went up to 650 units in 1984 with an increment of 230 units. It then went up to 1000 units in 1985 with an increment of 450 units from the year before, to 1500 in 1986 with an increment of 500 units, to 2200 in 1987 with an increment of 700 units....One can thus observe that not only production has been constantly increasing from 1983 to 1990 but also increments have been increasing themselves every year during the same period and that, furthermore, the rate of increase has been itself constantly increasing . . ."

Anybody will find grasping and understanding through (b) much easier than through (a). In the first case one must decode verbal symbols extracting their referents, keep in memory the successive pieces thus processed, mentally compare them and, eventually, "assemble" the overall structure. Nothing of this sort happens in the second case: one looks at the graph and "sees" this structure: increase in production, rates of increments, changes in the rate of increments, and so on are directly "perceived" as they are in their reciprocal relationships and do not have to be mentally reconstructed or assembled. The crucial limitation of the linear structure of the textual form also clearly emerges from the arbitrariness involved in the mapping process. Rather than (a) above, we could have (a'):

(a') "Production steadily increased in the years from 1983 to 1990, going from 420 to 650 to 1000 to 1500 . . . . to 9500, respectively in each year. During the same period increments have been themselves constantly growing , going from 230 units between the first and the second year to 450 between the second and the third, to 500 between the third and the fourth . . . . They have been especially strong during the last three years . . ."

There is no principled way of choosing between these two (or among the several) possible textual forms: since the structure of the field to be communicated is not linear, forcing it into a linear form will always involve non-univocal, arbitrary choices. On the other hand, since the line graph matches the structure of the knowledge field, its form is univocally determined and non- arbitrary. Examples can be easily multiplied by changing the knowledge field. Suppose this is of spatial nature, then one can compare the textual form with another kind of communicative form: the so- called "plan" or "map", as in (c) below.

There is no need of formulating here the textual form: anybody can do it for himself and compare its effects on understanding with (c). They will be similar to, though larger than, those noted for (a) and (b) above, since the knowledge field is in this case slightly more complex and richer. The important point is that here too the structure of the communicative form (c) matches (is isomorphic to) that of the knowledge field, and hence one can see and grasp it directly, rather than having to reconstruct it mentally from the linear succession of a textual description.

One could object that such transparent, isomorphic communicative forms (such as the line graph or plan showed above), though much more appropriate than the textual form, cannot be applied to much larger, richer and/or more complex knowledge fields: it is our contention that this is precisely what hypermedia systems allow us to do and should be used for. Our definition of hypermedia is, therefore, a structural one and not a content one: hypermedia in not hypertext whose "nodes" or documents belong to communicative media other than text, as commonly accepted in the literature (Nielsen, 1990). Rather, it allows the very structure of communication to be taken from media other than the linear text (such as 2D- or 3D-graphic design) and modelled on the structure of the knowledge field. How this can be done, we have tried to show by building a hypermedia system for a relatively large and rich knowledge field: that of descriptive geography. Since geographical knowledge is intrinsically structured in a spatial way (i.e., phenomena are organized in terms of relative locations, distances, dimensions, etc.), the communicative structure we choose to match this organization is that of a map. The result is HYPERMAP (Antinucci, 1992; Berlinguer, Meloni, Troise, 1992), the system we describe below together with the results of its testing. There are reasons to believe that a change in the structure of communicative form along the lines proposed here might strongly affect learning. When we talked above about differences in the cognitive process of understanding we used (informally) terms such as "decoding symbols", "referring", "mentally reconstructing and assembling" for the textual form, as opposed to "seeing", "perceiving", "grasping", etc. for the transparent isomorphic form of the line graph, plan, map. Psychologists (especially developmental psychologists) have long known the existence of two different modes of cognizing: a symbolic one and a sensorimotor one (Piaget, 1951; 1971; 1974). It is customary, however, to pay attention only to the first mode and associate "knowing", "thinking" with the symbolic mode. Many scientists and researchers in fields outside of psychology have repeatedly pointed out and stressed (often reflecting on their own experience) the role of what as been called "non-verbal", "non-symbolic" or "visual thinking" (Arnheim, 1969; Penrose, 1989; Ferguson, 1992). Correlated to these two different modes of cognizing, two different forms of learning have been traditionally recognized. One, variously termed "explicit", "declarative", "relational", etc., and the other, called "implicit", "nondeclarative", "habituational", etc. (a somewhat similar contrast is expressed by the phrases "learning that" and "learning how"). The prototypical cases of learning where these two forms can be easily contrasted are, for example, learning biological taxonomy vs. learning to ride a bycicle. Notice, in fact, that the first is explicit and step-by-step conscious: I can state declaratively what I learned and how I learned it . The second, on the other hand, is implicit and largely unconscious: I learn but I cannot describe what I learned or the process through which I learned. Traditionally, it has been assumed that these two forms are dependent, as in the example quoted above, upon the nature of the object that is to be learned: notions (biological taxonomy) vs. abilities (riding a bycicle). Both the literature on non-verbal, non-symbolic cognitive processing (such as that quote above) and recent research on memory and learning (Squire, 1992; Berry and Broadbent, 1988) tend to show that this concept is wrong and that a most important factor (though not the only one) in determining the form of learning is precisely what we have called the communicative form. Which of the learning mechanisms is activated does not depend on the "content" but rather on the form through which it is represented: implicit learning, if this form allows (or favours) sensorimotor processing; explicit learning, if it requires symbolic processing. Notice that this phenomenon is well known for a class of "objects" of learning that, though notion-like, have some perceptual and motor component. One example is learning to operate and program a videotape recorder. If the form in which this knowledge content is communicated is a booklet of instruction, I'll be forced to use the explicit learning mode. If this form, is whatching somebody who actually operates the VTR or (even better) observing the results of my own trying to operate it directly, then learning will be channelled through the implicit mode. The problem is that almost all notional fields of knowledge are today communicated through the "booklet" form. Changing the communicative form along the lines described above through the use of hypermedia systems, might, then, shift the learning process to the implicit mode with respect to knowledge fields that have always been the object of explicit learning only, thus making their acquisition more similar to the learning of abilities. The consequences of this shift might have great relevance for teaching and instruction: implicit learning tends to be much more powerful, effortless and less sensible to background and individual variations. First results obtained in testing learning through our hypermedia system HYPERMAP in a real school environment seem, as we shall see below, to support this statement.

HYPERMAP

Testing HYPERMAP

Subjects and procedure

Results

Results on the spatial ability task of matching country names to the mute map show a trend closely similar to the one discussed above. Experimental subjects passed from a mean score of 17.1 to 22.4 (increment: 31%), while control subjects passed from a mean score of 20.4 to 23.9 (increment: 17%). The ANOVA performed on these data shows, beyond a significant improvement in performance of both groups (dof 1, 80, F = 63,6, p < .0001), an interesting effect of treatment, plotted in the figure below, which approaches statistical significance. This effect mirrors in differences between groups assessed with Tukey HSD test: they are significant in pre- test condition (p = .0004), but they are not in post-test condition (p = .21).

Thus, the increase in performance of the experimental group tends to be significantly higher than that of the control group, as shown in Figure 2 above. Furthermore the same effect of a higher reduction of inner variance in the experimental group is present also in this task: SD decreases from 8.8 to 6.8 in the experimental group, while it decreases from 7.8 to 7.1 in the control group. It is interesting to note that a difference in performance increment occurs also when considering the subset of countries not directly studied. From pre-test to post-test, the capacity of locating correctly these countries passes from a mean score of 10.5 to 12.5 in the experimental group (increment: 19.1%), and from a mean score of 12.6 to 13.7 in the control group (increment: 8.7%).

Discussion

References

Antinucci, F. (1993).
Summa Hypermedialis (Per una Teoria dell'Ipermedia). Sistemi Intelligenti, 2: 227-257.

Arnheim, R. (1969).
Visual Thinking. University of California Press, Berkeley.

Berlinguer, L., Meloni, D., Troise, A. (1992).
Ipermappa. Golem, 11: 15-20.

Berry, D.C., Broadbent, D.E. (1988).
Interactive Tasks and the Implicit-Explicit Distinction. British Journal of Psychology, 79: 251-272.

Ferguson, E.S. (1992).
Engineering and the Mind's Eye. The MIT Press, Cambridge.

Nielsen, J. (1990).
Hypertext and Hypermedia. Academic Press, New York.

Penrose, R. (1989).
The Emperor's New Mind. Oxford University Press, Oxford.

Piaget, J. (1951).
Play, Dreams and Imitation. Norton, New York.

Piaget, J. (1971).
The Construction of Reality in the Child. Ballantine Books, New York.

Piaget, J. (1974).
The Origins of Intelligence in Children. International University Press, New York.

Squire, L.R. (1992).
Memory and the Hyppocampus: A Synthesis from Findings with Rats, Monkeys and Humans. Psychological Review, 99: 195-231.

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