Flexibility
Various cognitive psychologists have used the computer metaphor to characterize the human mind. According to this approach, the brain is the hardware and the mind is the software.
The analogy has generally been quite unfortunate and has been of little help to cognitive science, as the differences between brain and computer are far more important than the similarities. For the topic at hand, there are two essential differences. The first has to do with meaning. The second has to do with flexibility. Let's briefly examine each of them.
The essence of the mind is its unlimited capacity for interpretation. The brain has a conceptual memory in which concepts and meanings are stored. We speak of semantic memory. In this way, the mind thinks through associations of semantic fields. When we think of a dog, for example, we associate its meaning with domestic animals, barking, and various breeds of dogs; but also by association with cats, dog owners, and housekeeping, as Luria demonstrated in his profound text Consciousness and Language (1995: 58). Neuroscience calls this quality "diffuse activation." And anyone who carefully follows a conversation between a group of people, without participating in it, will see that we very frequently move from one topic to another, since the mind associates an idea or image with multiple ideas and images. Surely, the more creative or scattered some of the participants in the dialogue are, the more they tend to distance themselves from the idea that triggered the dialogue. Therefore, in a dialogue, it is often necessary to draw attention to the initial topic being discussed, because it is much more common than we think to get lost in dialogue.
The problem in this regard is that the computer analogy diverted reflection on the cognitive revolution toward relatively marginal problems, as Bruner argues. Rather than continuing to focus on the role of meaning, learning, and the mind, as was its initial impetus, the cognitive revolution fostered by Piaget, Chomsky, Bruner, and Kuhn, among others, shifted toward essentially technical reflections, weakening the research on the mind as a "black box" previously formulated by behaviorists. Even some former behaviorists welcomed this trend and adapted their stimulus-response models to the new input-output model formulated by the emerging theories of information processing theory (Bruner, 1990; 24-30).
The second problem with the brain-computer analogy has even more to do with the topic that brings us together in these lines: flexibility. The computer is the antithesis of flexibility, insofar as flexibility is an essential and defining characteristic of the human brain. Searching for something on a computer is generally traumatic because, despite its enormous memory, its inflexibility demands that the name of the program, song, or file being searched must be identical. Minor spelling, grammatical, or memory errors render the search completely fruitless. The computer can only associate A with A and 1 with 1, but it can't grasp that both are systems that begin numbering, even if one uses a letter and the other a number.
On the contrary, the flexibility of the mind is enormous thanks to brain plasticity. Plasticity is associated with changes in the number, type, and connection between neurons. The human brain has about ten billion neurons, and the cerebellum has ten to one hundred billion. Synapses are the process by which neurons connect and transmit information to each other. A typical neuron has tens of thousands of synapses. Therefore, neuronal plasticity also and especially involves synaptic plasticity. The nervous system maintains, throughout the life of the organism, the capacity for anatomical and functional modification according to stimuli from the environment. And this modifiability is responsible for the adaptive flexibility of organisms (Nieto in Mora et al., 2002: 67). It was also this plasticity that led Feuerstein to postulate his original thesis on the identity of intelligence and modifiability, which allowed him to formulate his thesis of human modifiability, his diagnosis of cognitive potential, and his Instrumental Enrichment program.
Strictly speaking, flexibility is an emergent property of competency-based learning in education. And it is emergent because competencies, being integral learning processes, necessarily imply flexibility.
Just as Ausubel (2002: 38) concludes that all meaningful learning involves transfer, we can conclude that all integral learning involves developing flexibility, since by modifying the initial structure, new learning processes can be used in various settings and contexts.
This is why Varela is absolutely right when he concludes that the best example of intelligence is not that of the chess player but that of the baby, since the player only responds to fixed rules in a world that does not move, and therefore, his task is extremely simple since it essentially consists of calculating well. On the contrary, what the baby does is much more complex, as he must adapt flexibly to a complex and hypermobile world in every sense. The infant faces uncertainty, while the chess player only requires very careful calculations, but in a stationary world. This is why the best chess player in the world can be beaten by a computer, while no computer can, for the time being and likely for many years to come, beat an infant in the complexity of the intellectual activities it performs.
Vindicating flexibility as an emergent property implies that all exams must ask about topics not explicitly addressed in the classroom, but that can be clearly and simply inferred from those explicitly mediated in class. It requires not accepting the identical definition of the concept we want to assess as the one that appears in the textbook or that was indicated in class. It demands formulating novel problems and expecting equally novel answers. It necessarily requires the transfer of knowledge to other areas. And therefore, an excellent way to assess competencies is to hypothetically assume the nonexistence of the concept we are addressing in class (be it matter, weight, energy, or gravitational force, to name a few examples from the natural sciences) and investigate the consequences of this possibility for human life. What would happen to human life on Earth without gravity?
If we want to assess flexibility, we will have to work on it in class, creating the conditions for new questions to emerge. Therefore, the Harvard team's recommendation of generative topics is pertinent, as these allow for multiple associations and connections to be found and invite exploration (Blythe et al., 1999: 58). In any case, it seems necessary to insist on the convenience of using diverse discursive methods to approach topics in mediation processes, reading authors who offer diverse explanations and who, to the extent possible, use different and preferably contradictory theoretical frameworks. In class, we must argue and counter-argue the same ideas; we must always find the strengths and weaknesses of the theories studied. And we must analyze all of them—as Merani used to say—with the “Socratic sting of intelligence.”
Flexibility is also expressed in graphic representation, and to foster it, it is necessary to use multiple representations of the propositions, concepts, and conceptual chains we use. Using a single diagram, such as a concept map, mind map, or SVU diagram, has a negative effect on the flexibility and diversity of thought. This is why we share Davidov's thesis, who urges us to be wary of schemes that restrict and dogmatize thought. In his words (Davidov, 1975: 28):
It is not possible to assume that a single set of substantial attributes exists to define a concept: the choice of essential features—to form the definition—is not univocal across all cases.
In reality, the location of the essence of a concept depends on the frame of reference and the context. Hence, it must necessarily be diverse. If this is true at the conceptual level, it is even more so at the level of representation. To this end, Aristotelian definitions should be used (using genre and specific difference), by exclusion, conceptual pyramids, or operational definitions if necessary (De Zubiría, 2006a: 225). It is also necessary to expand and diversify representations using, for example, double-entry matrices, synoptic tables, conceptual pyramids, concept maps, SVU diagrams, mind maps, and mind maps, among others.
A school that worships homogenization cannot foster flexibility. Instead, we need schools that subject any dogma of any kind to criticism: religious, political, cultural, or scientific. A school that accepts that its role is formative and therefore recognizes the cultural, historical, contextual, and relative nature of all positions at all times. And we need to create multiclass, multiracial, multicultural schools, in which teachers represent the widest possible range of ideologies, religions, and paradigms. As can be seen, in Latin America we are still far from creating the conditions to guarantee flexibility in schools and universities.