Por que Espiritismo é Educação?

Terá de haver um fator de igualação. Algo de comum e essencial aos dois conceitos. Procuremos esse fator. Ora, educar vem do latim "educere" que significa tirar, extrair (de dentro) de alguma coisa (e = fora; ducere = conduzir). Portanto, educar é conduzir para fora. Para fora do quê? Para fora do íntimo, do fundo, do espírito, do educando. Mas conduzir o quê para fora do educando? Conduzir as suas perfeições que jazem no fundo de sua alma, e aí permanecem em estado potencial, aguardando sua atualização. Processo esse de atualização (realização) que nada mais é do que educação (conduzir para fora).

Por outro lado, o Espiritismo também visa a essa emersão de todas as aptidões que Deus depositou no âmago de nossa alma no ato que criou nosso espírito. E da mesma forma, em estado potencial, cabendo a cada Espírito assim criado o esforço íntimo de promoção (auto-educação) desse afloramento das perfeições ou virtudes. Esse processo educativo se resume no fim individual da Educação Espírita que é Desenvolvimento da Espiritualidade também conhecido pela expressão Reforma Íntima (contínua). O conjunto de nossas perfeições em estado potencial é enfeixado na expressão Perfectibilidade que é a mesma Espiritualidade em estado latente.

Conclusão: o fator de igualação procurado entre Espiritismo e Educação é o Desenvolvimento da potencialidade da alma (Reforma Íntima), comum tanto a um quanto ao outro conceito.

[Espiritismo e Educação, cap. "A força docente da 
Doutrina Espírita", pág. 39 - Ney Lobo]

Encarnação, Reencarnação e Educação

A encarnação procura responder à pergunta: para que (futuro) encarnamos? Ela focaliza o presente, mas o presente voltado para o futuro.

A reencarnação procura responder à pergunta por que (passado) reencarnamos? Focaliza o passado, mas o passado projetado no presente.

Segundo o enfoque encarnatório - como ele se acha conceituado acima - a educação representa o processo (auto ou hetero) de afloramento das perfeições que jazem no acervo potencial do espírito de cada encarnado.

[Na perspectiva reencarnatória], educar consitirá em induzir o educando a: 1º - aceitar os seus infortúnios atuais com resignação como consequências dos desvios evolutivos pretéritos; 2º - assumir a responsabilidade por essas ações cometidas no uso do seu livre-arbítrio; 3º - predispor-se à reparação desses desvios.

[Espiritismo e Educação, cap. "Estudo espírita da unidade 

educacional encarnação / reencarnação", págs. 21, 22 e 25 - Ney Lobo]

Science as Collaborative Search

The kind of decision processes instantiated in both the binary and realvalued particle swarm algorithms exemplify a tendency that has been widely regarded as a flaw or error when seen in human cognition. Karl Popper (1959) revolutionized scientific methodology by persuading us that it is impossible to confirm a hypothesis—it is only possible to disprove one. In his famous example, even if you have seen a million white swans, and never in your life have you seen any other color, you still have not conclusively proven that “all swans are white.” On the other hand, a single black swan will disprove the statement. Modern scientific methodology is based on the philosophy of null hypothesis testing, which takes the tack of trying to prove the hypothesis that your research hypothesis is in fact false, that is, you look for black swans. A hypothesis cannot be tested unless it is falsifiable, and scientific proof relies on identifying what would happen if the hypothesis were indeed false and then discovering if those events occur in an experimental situation.

While it is logically impossible to prove a hypothesis by accumulating support for it, this is exactly the approach people normally take. Cognitive psychologists call this tendency confirmation bias, the propensity to irrationally seek confirmation for our beliefs, rather than falsification. Klayman and Ha (1987) turned the issue around by pointing out that falsification is not a good strategy for determining the truth or falsehood of many hypotheses. They proposed that people tend to use a “positive test strategy,” which is defined as testing cases that are expected to produce the hypothesized result, rather than testing cases that are intended to fail to produce it. They suggested that people use the positive test strategy (+testing) as a default heuristic. Further, they noted that “as an allpurpose heuristic, +testing often serves the hypothesis tester well” (p. 225).

Another way of looking at this is to compare truth and certainty. Most of the time, people solving  a problem don’t require knowledge that something be established as true; they only require that it be established to a level of certainty. As Karl Popper said in a recent interview with writer John Horgan (1996), “We must distinguish between truth, which is objective and absolute, and certainty, which is subjective.” Adjusting your hypotheses toward the consensus position and testing cases that confirm what you already believe are methods for increasing the sense of certainty. One thing that will undermine that sense is of course contradiction by empirical facts; thus, “+testing” can only work if it is consistent with phenomena in the world. While it is possible to build up certainty in the absence of truth, the two are not independent—a fact that can be capitalized on. Strategies that increase certainty may be likely to discover truths as well.

In the model we have just described, individuals move toward their previous successes; confirmation bias is fundamental to this strategy. But this is an elaborated, social confirmation bias: individuals seek to confirm not only their own hypotheses but also those of their neighbors. Paradoxically, though we may be pointing out that people are not very scientific in their thinking, especially insofar as science is supposed to be mathematical and deductive, even scientists act like this. What Thomas Kuhn (1970) calls a paradigm is a kind of confirmatory social convergence of scientists in a theoretical decision space: “A paradigm is what the members of a scientific community share, and conversely, a scientific community consists of men who share a paradigm” (p. 176). The scientists come to agreement on the use of terminology, acceptable research methods, and other aspects of their work, and it is by intense communal focus on a narrowly defined subject domain that the scientists are able to fully exploit the learning that has preceded them. In the particle swarm analogy, a Kuhnian “revolution” occurs when an individual finds a better region of the search space and begins to attract its neighbors toward it by becoming the best in the neighborhood.

In the 1960s and 1970s some evolutionary theorists began to propose a correspondence between scientific and evolutionary processes that continues to be reiterated (Campbell, 1965, 1974; Popper, 1972; Lorenz, 1973; Atmar, 1976; Dawkins, 1987). In this view, an individual member of a species represents a hypothesis about the logical properties of the environment; the validity of the hypothesis is shown by the survival of the individual. This inductive approach to learning leads to constantly improving prediction of the important aspects of the environment. As in previous discussion of the memetic view, our objection to the too-literal acceptance of this view has to do with the difference between selection, as it occurs in evolution, and change as it appears in learning. A scientist often has a long career spanning the comings and goings of multiple paradigms. Hypotheses are ideas that are held in the minds of scientists, who are able through constant refinement, through constant adaptatio —through learning—to improve the validity of their hypotheses. The evolutionary perspective looks at the mutation and selection of ideas per se, while the particle swarm view looks at the adaptive changes of individuals who hold those ideas.

In informal human social search of a problem space, little effort is typically made to carefully choose data, and both measurement and sampling error are extremely plentiful—a glance through any textbook in social or cognitive psychology will reveal dozens of “heuristics,” “biases,” and “errors” in human information processing. We propose that many of the biases result from the “particle swarm” tendency of individuals to move toward self- and social confirmation of hypotheses—a tendency that, while logically invalid, in fact results in excellent information-processing capabilities. We don’t agree that human thinking is faulty; we suggest on the contrary that formal logic is insufficient to solve the kinds of problems that humans typically deal with.

[Swarm Intelligence, cap. 7: "The Particle Swarm" - James Kennedy e Russel C. Eberhart]