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The problem

At the center of attention of the concept maps users community there has always been the concern about the map "access point", the point to start "reading" the map from, from which to start analyzing its contents.

The primitive criteria about maps (those more diffused, though already widely overcome, and in some aspects also denied) by the developments in technology and in cognitive psychology itself, proposed this role of the "more important concept" ("m.i.c", that is usually translated into a big red colored  symbol)... a unique milestone that, "just by chance", usually bears the same name of the map. This "m.c.i." must be defined by the author and/or must be placed at the top of a hierarchy, but concept maps are not hierarchical.


In practice (as well as in theory), this approach fails, it becomes more of an obstacle than a useful method. And reasons are very simple:
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A concept map or semantic network has always more than one "important" concept, that is worth special attention.

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As importance by itself is relative, it is very difficult to define "that" concept. Furthermore, it is always preferable to depend on a demonstration or on a rational formulation than on a definition.

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The same happens with the definition of several "important concepts" in the same map.

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In the map, a concept by itself  has a relative value, its relativity relies on several factors (the most important one is the student himself), and its value depends on its relations and on its information load (its descriptions, Internet links, associated documents, multimedia, etc.).

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If among the great virtues and characteristics of concept mapping and semantic networking there is the  avoidance of the difficulties imposed by text reading and decoding, to facilitate  perception, comprehension and reasoning, transferring to the map the same principles of text reading (the organization in phrases or paragraphs and the reading start and end points), this means depriving the maps of the "conceptual" and "cognitive" principles; the quality of knowledge representation and its corresponding management loses power, value and usefulness.

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In a real map, with more than a few concepts, its analysis following the "m.i.c." indications is rendered more complex and misleading: if all reading tracks start from the "important concept", there will be paths (elements of crucial importance) that will never be analyzed. Therefore, some important cognitive values are lost.

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The "m.i.c." approach conspires against two main principles of comprehension: map management ergonomics and cognitive economy: from one side we are induced/compelled to follow constrained paths, that have the same start concept, and from another side a conscious and detailed analysis of contents would require  more time and effort (if we stick to the "m.i.c" approach).

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The presence of the "m.i.c." and its graphical distinction collides with the concept categories: it appears  as a category when it really isn't. A s a matter of fact, instead of  having an orientation role, the presence of "m.i.c." is confusing, because it simply doesn't make sense, it's not practical.

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Having to define the "m.i.c."  is a responsibility that can be avoided.

As the map must induce a reflection in the learner, and the map admits many of them, in theory any map node is useful to start analyzing; beside concept categories, concepts instances, or nodes that have associated documents, Internet sites, concepts resulting from internal searches, etc., that enable expansion and deeper insight or the candidate nodes to a preeminent role can mainly be those more connected. In any case, the user (be it a primary school student or a researcher), to analyze the maps, relies on his/her observation abilities (of "looking at and recognizing"). But these observational abilities are not equal for all people; one of the biggest successes of this technology is precisely a qualitative and quantitative improvement of learning, that enables everyone, including people considered as learning "disadvantaged" or "impaired" or that have a certain degree of dyslexia or ADD (Attention Deficit Disorder), or that simply learn in some other way. However, regarding concept maps/semantic networks looking or observing is not enough. As the challenging street jugglers and illusionists say: "the more one looks, the less one sees".

In the experiments, even with people with medium to high computer knowledge qualification, when for the first time they face or analyze a concept map or semantic network, the first thing they say is: "Where do I start from?".

The solution

The solution is simple, automatic and auto-validating, and refers to the principles of cognitive psychology.

At whichever level it happens, in the classroom, at a distance, in scientific research or as knowledge management in a company, learning always occurs through a communication activity, and consists of (in?) an information elaboration and integration process. For this, cognitive psychology offers an interesting principle: relevance (cognitive and communicative). In communication, the mind wants to comprehend the message, to comprehend the contents it conveys, what is interesting, new or coherent (in this case in the map), in what way this novelty (the new information) finds a point of contact with our current knowledge, in which measure it can activate some already present element (any resemblance with the Ausubelian principle of cognitive precedence is not pure coincidence).

This new approach induces a characterization of the relevance principle in a concept map or semantic network, already outlined in the research in cognitive psychology some years ago. The most relevant concepts or nodes in the map are those that constitute more propositions, those that receive and/or emit more relations, that is in resonance with the role of relations as carriers of knowledge in concept maps and semantic networks.

Considering the most relevant concepts as the natural points to start analyzing the map structure,  the following advantages are offered:

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It helps to overcome the initial inertia ("where do I start from?") in accessing the map contents.

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Being these concepts the most connected, accessing the map through these nodes (or concepts) will  require a lower quantity of "readings"/analysis, for reasoning and comprehending the whole map; from these "most relevant" concepts it is easier to access and navigate the rest of the map with the minimal amount of accesses.

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It is said that the concept map / semantic network facilitates and somehow speeds up learning. With this principle, it really accelerates it.

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The necessary time to process contents (to understand and integrate) decreases very fast, interaction with contents is rendered more effective.

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The learner's interaction with the map becomes more interesting and amusing.

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Being the most relevant nodes those that most probably will take part in semantic paths in the map, this coincidence legitimates the method.

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It is useful with any contents and with students of any age.

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It is a fully automatic function, just a click.

But the observational ability varies from person to person. When the map tries to represent, for instance, a comparison of two objects, it should be evident at first glance which the focal nodes are (another way of denominating the most relevant concepts) due to the concentration of relations. In other maps, it can also be evident which those concepts are, but not always and not all of them.


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In the map at right, it is evident which are both focal nodes in the comparison of two objects ("hypertext" and "concept map"), that the author of the map has expressly wanted to put in evidence. It is obvious that by analyzing "only" both concepts (their propositions) the whole map is analyzed. The result is the same when the most relevant concepts are more than two, and even when relevance is not graphically so much perceptible (it usually isn't).

 
The solution is  technological

Knowledge Master automatically evaluates the  most relevant concepts in the map, and presents them by order of relevance, starting from the most relevant. When presented, every concept blinks in the map "saying" (literally, with a voice) its name.

A list of all concepts that have been considered over the relevance threshold remains available to the user, in order of relevance, and two buttons. With the buttons, it is possible to locate concepts sequentially, to analyze in each one its own context.

From the list it is possible to directly select any concept, to access it in one of these modes:

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"Localization": the concept blinks, to let us locate it and proceed with analysis.

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"Presentation": a new context is activated with the full selected concept neighborhood, the list of all of its propositions, just as if we had asked the map "What do you know about (the concept)?". The map sector in which the concept is located is presented to the user. The presentation has a voice support for better perception.

The function, a knowledge management strategy applied to learning, analyzes and presents a sector of the cognitive structure, in a way that corresponds to the natural characteristics of the mind, it resorts mainly to the characteristics of human perception and to the working memory capacity, and demonstrates its efficacy enabling the analysis of the map in the simplest mode, saving time and effort. The fact that it uses voice synchronically, transcends the normal perception threshold, using contemporarily the voice channel and the visual channel. This strategy, even though it is simply a general learning resource, is specially effective on people affected by dyslexia, ADD (Attention Deficit Disorder) and by some other limitations associated with traditional learning/teaching methods. In many cases, this technology might be "the" solution.

The automatic measurement and use of the relevance method has a strong contextual effect (the main elements are accurately understood) and reduces the processing effort: the greater the contextual effect, the less will be the necessary effort to comprehend and assimilate information; the greater the information relevance, will be processed in a more productive way, promoting learning.

 

The metaphor that assists this method is that of the railway nodes.

The paradox is that a concept considered fundamental by the author (from the cognitive point of view) might not be recognized as such (which means that something lacks in the map). The automatic relevance analysis result is an important indicator for the map author, who this way is able to control  the map contents and organization. For the teacher/professor, for the researcher and for the student (a child in the classroom or an adult as a distance learner) it is a powerful resource for learning and research, that pushes the learning technology standards ahead.

 

All the theories and demonstrations..., when the only thing we must do is click twice!

 

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