Stereotypically, computation involves intrinsic changes to the medium of representation: writing new symbols, erasing old symbols, turning gears, flipping switches, sliding abacus beads. Perspectival computation leaves the original inscriptions untouched. The problem solver obtains the output by merely alters his orientation toward the input. There is no rewriting or copying of the input inscriptions; the output inscriptions are numerically identical to the input inscriptions. This suggests a loophole through some of the computational limits apparently imposed by physics. There can be (...) symbol manipulation without inscription manipulation because symbols are complex objects that have manipulatable elements besides their inscriptions. Since a written symbol is an ordered pair of consisting of a shape and the reader's orientation to that inscription, the symbol can be changed by changing the orientation rather than inscription. Although there are the usual physical limits associated with reading the answer, the computation is itself instantaneous. This is true even when the sub-calculations are algorithmically complex, exponentially increasing or even infinite. (shrink)

Computation is interpretable symbol manipulation. Symbols are objects that are manipulated on the basis of rules operating only on theirshapes, which are arbitrary in relation to what they can be interpreted as meaning. Even if one accepts the Church/Turing Thesis that computation is unique, universal and very near omnipotent, not everything is a computer, because not everything can be given a systematic interpretation; and certainly everything can''t be givenevery systematic interpretation. But even after computers and computation have been (...) successfully distinguished from other kinds of things, mental states will not just be the implementations of the right symbol systems, because of the symbol grounding problem: The interpretation of a symbol system is not intrinsic to the system; it is projected onto it by the interpreter. This is not true of our thoughts. We must accordingly be more than just computers. My guess is that the meanings of our symbols are grounded in the substrate of our robotic capacity to interact with that real world of objects, events and states of affairs that our symbols are systematically interpretable as being about. (shrink)

At present, the prevailing Connectionist methodology forrepresenting rules is toimplicitly embody rules in neurally-wired networks. That is, the methodology adopts the stance that rules must either be hard-wired or trained into neural structures, rather than represented via explicit symbolic structures. Even recent attempts to implementproduction systems within connectionist networks have assumed that condition-action rules (or rule schema) are to be embodied in thestructure of individual networks. Such networks must be grown or trained over a significant span of time. However, arguments (...) are presented herein that humanssometimes follow rules which arevery rapidly assignedexplicit internal representations, and that humans possessgeneral mechanisms capable of interpreting and following such rules. In particular, arguments are presented that thespeed with which humans are able to follow rules ofnovel structure demonstrates the existence of general-purpose rule following mechanisms. It is further argued that the existence of general-purpose rule following mechanisms strongly indicates that explicit rule following is not anisolated phenomenon, but may well be a common and important aspect of cognition. The relationship of the foregoing conclusions to Smolensky''s view of explicit rule following is also explored. The arguments presented here are pragmatic in nature, and are contrasted with thekind of arguments developed by Fodor and Pylyshyn in their recent, influential paper. (shrink)

In this article, we explore how digital marketers think about marketing in the age of Big Data surveillance, automatic computational analyses, and algorithmic shaping of choice contexts. Our starting point is a contradiction at the heart of digital marketing namely that digital marketing brings about unprecedented levels of consumer empowerment and autonomy and total control over and manipulation of consumer decision-making. We argue that this contradiction of digital marketing is resolved via the notion of relevance, which represents what Fredric (...) Jameson calls a symbolic act. The notion of the symbolic act lets us see the centering of relevance as a creative act of digital marketers who undertake to symbolically resolve a contradiction that cannot otherwise be resolved. Specifically, we suggest that relevance allows marketers to believe that in the age of surveillance capitalism, the manipulation of choice contexts and decision-making is the same as consumer empowerment. Put differently, relevance is the moment when marketing manipulation disappears and all that is left is the empowered consumer. To create relevant manipulations that are experienced as empowering by the consumer requires always-on surveillance, massive analyses of consumer data and hyper-targeted responses, in short, a persistent marketing presence. The vision of digital marketing is therefore a fascinating one: marketing disappears at precisely the moment when it extends throughout the life without limit. (shrink)

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their (...) shapes, be grounded in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

Symbolic arithmetic is fundamental to science, technology and economics, but its acquisition by children typically requires years of effort, instruction and drill1,2. When adults perform mental arithmetic, they activate nonsymbolic, approximate number representations3,4, and their performance suffers if this nonsymbolic system is impaired5. Nonsymbolic number representations also allow adults, children, and even infants to add or subtract pairs of dot arrays and to compare the resulting sum or difference to a third array, provided that only approximate accuracy is required6–10. Here (...) we report that young children, who have mastered verbal counting and are on the threshold of arithmetic instruction, can build on their nonsymbolic number system to perform symbolic addition and subtraction11–15. Children across a broad socio-economic spectrum solved symbolic problems involving approximate addition or subtraction of large numbers, both in a laboratory test and in a school setting. Aspects of symbolic arithmetic therefore lie within the reach of children who have learned no algorithms for manipulating numerical symbols. Our findings help to delimit the sources of children’s difficulties learning symbolic arithmetic, and they suggest ways to enhance children’s engagement with formal mathematics. We presented children with approximate symbolic arithmetic problems in a format that parallels previous tests of non-symbolic arithmetic in preschool children8,9. In the first experiment, five- to six-year-old children were given problems such as ‘‘If you had twenty-four stickers and I gave you twenty-seven more, would you have more or less than thirty-five stickers?’’. Children performed well above chance (65.0%, t1952.77, P 5 0.012) without resorting to guessing or comparison strategies that could serve as alternatives to arithmetic. Children who have been taught no symbolic arithmetic therefore have some ability to perform symbolic addition problems. The children’s performance nevertheless fell short of performance on non-symbolic arithmetic tasks using equivalent addition problems with numbers presented as arrays of dots and with the addition operation conveyed by successive motions of the dots into a box (71.3% correct, F1,345 4.26, P 5 0.047)8.. (shrink)

The symbol grounding problem is concerned with the question of how the knowledge used in AI programs, expressed as tokens in one form or another or simply symbols, could be grounded to the outside world. By grounding the symbols, it is meant that the system will know the actual objects, events, or states of affairs in the world to which each symbol refers and thus be worldly-wise. Solving this problem, it was hoped, would enable the program to understand (...) its own action and hence be truly intelligent ). The problem becomes more acute after a challenge posed by Searle in his now famous Chinese Room Gedanken experiment. Searle argued that no AI programs can be said to understand or have other cognitive states, if all they do is formal symbol manipulation. (shrink)

On the occasion of a first conference on Cognitive Science, it seems appropriate to review the basis of common understanding between the various disciplines. In my estimate, the most fundamental contribution so far of artificial intelligence and computer science to the joint enterprise of cognitive science has been the notion of a physical symbol system, i.e., the concept of a broad class of systems capable of having and manipulating symbols, yet realizable in the physical universe. The notion of (...) class='Hi'>symbol so defined is internal to this concept, so it becomes a hypothesis that this notion of symbols includes the symbols that we humans use every day of our lives. In this paper we attempt systematically, but plainly, to lay out the nature of physical symbol systems. Such a review is in ways familiar, but not thereby useless. Restatement of fundamentals is an important exercise. (shrink)

This book is a selection of papers from a conference which took place at the University of Keele in July 1982. The conference was an extraordinarily enjoyable one, and we would like to take this opportunity of thanking all participants for helping to make it so. The conference was intended to allow scholars working on different aspects of symbolic behaviour to compare findings, to look for common ground, and to identify differences between the various areas. We hope that it was (...) successful in these aims: the assiduous reader may judge for himself. Several themes emerged during the course of the conference. Some of these were: 1. There is a distinction to be made between those symbol systems which attempt, more or less directly, to represent a state of affairs in the world (e. g. language, drawing, map and navigational skill) and those in which the representational function is complemented, if not overshadowed, by properties of the symbol system itself, and the systematic inter-relations that symbols can have to one another (e. g. music, mathematics). The distinction is not absolute, for the nature of all symbolic skills is, in part, a function of the structure of the symbolic system employed. Nonetheless, this distinction helps us to understand some common acquisition difficulties, such as that experienced in mathematics, where mental manipulation of symbols can go awry if a child assumes too close a correspondence between mathematical symbols and the world they represent. 2. (shrink)

The core of the language of thought program is the claim that thinking is the manipulation of symbols according to rules. Yet LOT has said little about symbol natures, and existing accounts are highly controversial. This is a major flaw at the heart of the LOT program: LOT requires an account of symbol natures to naturalize intentionality, to determine whether the brain even engages in symbol manipulations, and to understand how symbols relate to lower-level neurocomputational states. (...) This paper provides the much-needed theory of symbols, and in doing so, alters the LOT program in significant respects. (shrink)

Corporative global media cannot be an instrument of the culture of peace, because they have made widespread individualistic values of the consummative society. Through their symbolic power, they successfully dominate over every sphere of existence of a society: politics, economic life, social ties, national culture, human communication and private life. Traditional media could not be a factor in the promotion and development of culture of peace, simply because they are proponents of corporative economic and political interests. It is in the (...) interest of citizens to counter the activities of “rapacious capitalism” (SCHMIDT 1998), of local comprador political and economic elites, and the practice of robbery of their work; to bridle the proliferation of weapons and acts of aggression. (shrink)

The ancient dualism of a sensible and an intelligible world important in Neoplatonic and medieval philosophy, down to Descartes and Kant, would seem to be supplanted today by a scientific view of mind-in-nature. Here, we revive the old dualism in a modified form, and describe mind as a symbolic language, founded in linguistic recursive computation according to the Church-Turing thesis, constituting a world L that serves the human organism as a map of the Universe U. This methodological distinction of L (...) vs. U helps to understand how and why structures of phenomena come to be opposed to their nature in human thought, a central topic in Heideggerian philosophy. U is uncountable according to Georg Cantor’s set theory but Language L, based on the recursive function system, is countable, and anchored in a Gray Area within U of observable phenomena, typically symbols, prelinguistic structures, genetic-historical records of their origins. Symbols, the phenomena most familiar to mathematicians, are capable of being addressed in L-processing. The Gray Area is the human Environment E, where we can live comfortably, that we manipulate to create our niche within hostile U, with L offering overall competence of the species to survive. The human being is seen in the light of his or her linguistic recursively computational mind. Nature U, by contrast, is the unfathomable abyss of being, infinite labyrinth of darkness, impenetrable and hostile to man. The U-man, biological organism, is a stranger in L-man, the mind-controlled rational person, as expounded by Saint Paul. Noumena can now be seen to reside in L, and are not fully supported by phenomena. Kant’s noumenal cause is the mental L-image of only partly phenomenal causation. Mathematics occurs naturally in pre-linguistic phenomena, including natural laws, which give rise to pure mathematical structures in the world of L. Mathematical foundation within philosophy is reversed to where natural mathematics in the Gray Area of pre-linguistic phenomena can be seen to be a prerequisite for intellectual discourse. Lesser, nonverbal versions of L based on images are shared with animals. (shrink)

Classical cognitive science assumes that intelligently behaving systems must be symbol processors that are implemented in physical systems such as brains or digital computers. By contrast, connectionists suppose that symbol manipulating systems could be approximations of neural networks dynamics. Both classicists and connectionists argue that symbolic computation and subsymbolic dynamics are incompatible, though on different grounds. While classicists say that connectionist architectures and symbol processors are either incompatible or the former are mere implementations of the latter, connectionists (...) reply that neural networks might be incompatible with symbol processors because the latter cannot be implementations of the former. In this contribution, the notions of 'incompatibility' and 'implementation' will be criticized to show that they must be revised in the context of the dynamical system approach to cognitive science. Examples for implementations of symbol processors that are incompatible with respect to contextual topologies will be discussed. (shrink)

People can be taught to manipulate symbols according to formal mathematical and logical rules. Cognitive scientists have traditionally viewed this capacity—the capacity for symbolic reasoning—as grounded in the ability to internally represent numbers, logical relationships, and mathematical rules in an abstract, amodal fashion. We present an alternative view, portraying symbolic reasoning as a special kind of embodied reasoning in which arithmetic and logical formulae, externally represented as notations, serve as targets for powerful perceptual and sensorimotor systems. Although symbolic reasoning often (...) conforms to abstract mathematical principles, it is typically implemented by perceptual and sensorimotor engagement with concrete environmental structures. (shrink)

According to "computationalism" (Newell, 1980; Pylyshyn 1984; Dietrich 1990), mental states are computational states, so if one wishes to build a mind, one is actually looking for the right program to run on a digital computer. A computer program is a semantically interpretable formal symbol system consisting of rules for manipulating symbols on the basis of their shapes, which are arbitrary in relation to what they can be systematically interpreted as meaning. According to computationalism, every physical implementation of the (...) right symbol system will have mental states. (shrink)

The concept of representation has become almost inextricably bound to the concept of symbol systems. the concepts is nowhere more prevalent than in descriptions of "internal representations." These representations are thought to occur in an internal symbol system that allows the brain to store and use information. In this paper we explore a different approach to understanding psychological processes, one that retains a commitment to representations and computations but that is not based on the idea that information must (...) be stored and manipulated in symbol systems. In particular, we suggest that the notion of a symbol system as currently understood construes psychological processes in terms of a specific type of computational system, in which a control function "reads," "interprets," and manipulates discrete entities called "symbols." We argue that other types of computational systems may provide a more appropriate characterization of psychological processes. One implication of our argument is the need to consider the constraints placed on computational theories in psychology by the nature of the computing device itself, the human brain. Perhaps surprisingly, this implication leads us to the conclusion that a "functionalist" conception of psychological processes (discussed below) does not entail that physiology is irrelevant to psychology, as has been maintained by prominent adherents of the symbol-systems approach. (shrink)

This chapter focuses on one historically important approach to computationalism about thought. According to "the classical computational theory of mind" (CTM), thinking involves the algorithmic manipulation of mental symbols. The chapter reviews CTM and the related language of thought (LOT) position, urging that the orthodox position, associated with the groundbreaking work of Jerry Fodor, has failed to specify a key component: the notion of a mental symbol. It clarifies the notion of a LOT symbol and explores an (...) approach different from the orthodox, Fodorian LOT/CTM. The LOT position is a leading approach to the computational nature of thought. A key feature of LOT is that its mental representations have a combinatorial syntax. A representational system has a combinatorial syntax when it employs a finite store of atomic representations, which can be combined to form compound representations, which can then be combined to form further compound representations. (shrink)

The well-known game of chess has traditionally been modeled in artificial intelligence studies by search engines with advanced pruning techniques. The models were thus centered on an inference engine manipulating passive symbols in the form of tokens. It is beyond doubt, however, that human players do not carry out such processes. Instead, chess masters instead carry out perceptual processes, carefully categorizing the chunks perceived in a position and gradually building complex dynamic structures to represent the subtle pressures embedded in the (...) positions. In this paper we will consider two hypotheses concerning the underlying subcognitive processes and architecture. In the first hypothesis, a multiple-leveled chess representational structure is presented, which includes distance graphs (with varying levels of quality) between pieces, piece mobilities, and abstract roles. These representational schemes seem to account for numerous characteristics of human player’s psychology. The second hypothesis concerns the extension of the architecture proposed in the Copycat project as central for modeling the emergent intuitive perception of a chess position. We provide a synthesis on how the postulated architecture models chess intuition as an emergent mixture of simultaneous distance estimations, chunk perceptions, abstract role awareness, and intention activations. This is an alternative model to the traditional AI approaches, focusing on the philosophy of active symbols. (shrink)

The article deals with `The Symbolic Force of Human Rights'. First, it restricts the meaning of the term `symbolic' and of the expression `symbolic force'. Second, it discusses the concept of human rights. Having established the conceptual framework, the author goes to the core of his argument, characterizing the symbolic force of human rights as ambivalent: on one hand, it serves for their generalized affirmation and accomplishment; on the other hand, it acts as a manner of political manipulation. In (...) this regard, the article focuses, first, on the symbolic force of human rights at the level of national states, and then within the international and worldwide context, on criticizing finally the rhetorical use of human rights by nowadays' only superpower, the USA. Key Words: human rights • interventionism • supranational and national • legal orders • symbolic force. (shrink)

This short paper grew out of an observation—made in the course of a larger research project—of a surprising convergence between, on the one hand, certain themes in the work of Mary Hesse and Nelson Goodman in the 1950/60s and, on the other hand, recent work on the representational resources of science, in particular regarding model-based representation. The convergence between these more recent accounts of representation in science and the earlier proposals by Hesse and Goodman consists in the recognition that, in (...) order to secure successful representation in science, collective representational resources must be available. Such resources may take the form of (amongst others) mathematical formalisms, diagrammatic methods, notational rules, or—in the case of material models—conventions regarding the use and manipulation of the constituent parts. More often than not, an abstract characterization of such resources tells only half the story, as they are constituted equally by the pattern of (practical and theoretical) activities—such as instances of manipulation or inference—of the researchers who deploy them. In other words, representational resources need to be sustained by a social practice; this is what renders them collective representational resources in the first place. (shrink)

In this way, his diffuse if not altogether random behavior is already action in the world, directed towards ends which he did not lay down and yet which satisfy his needs. The neonate is integrated in a system of immediate utility, and his body is surrounded by a complex of instruments, utensils, and commodities, never made or put there by him but nonetheless constituting the meaning of his objectivity. Hence his objectivity, or his body as a significant object, is constituted (...) by the activity of others. Although he has not himself made or given himself this meaning, it is what he is, for his needs are silenced and this is decided according to an empirical test of satisfaction as drive reduction. At the stage of immediate utility it cannot be maintained that the child's objectivity or the systematic interpretation of his behavior is forced upon him, since the system works and his needs are satisfied. We conclude, then, that his body is his being-for-others and that he is this body although he cannot pose it for himself; that is to say, he cannot manipulate and control the complex of instruments that surround him and thus give to his gestures the meaning they have for others. (shrink)

The aim of the paper is to present the underlying reason of the unsolved symbol grounding problem. The Church-Turing Thesis states that a physical problem, for which there is an algorithm of solution, can be solved by a Turing machine, but machine operations neglect the semantic relationship between symbols and their meaning. Symbols are objects that are manipulated on rules based on their shapes. The computations are independent of the context, mental states, emotions, or feelings. The symbol processing (...) operations are interpreted by the machine in a way quite different from the cognitive processes. Cognitive activities of living organisms and computation differ from each other, because of the way they act in the real word. The result is the problem of mutual understanding of symbol grounding. (shrink)

Contrary to the assumption of arbitrariness in modern linguistics, sound symbolism, which is the non-arbitrary relationship between sounds and meanings, exists. Sound symbolism, including the “Bouba–Kiki” effect, implies the universality of such relationships; individuals from different cultural and linguistic backgrounds can similarly relate sound-symbolic words to referents, although the extent of these similarities remains to be fully understood. Here, we examined if subjects from different countries could similarly infer the surface texture properties from words that sound-symbolically represent hardness in Japanese. (...) We prepared Japanese sound-symbolic words of which novelty was manipulated by a genetic algorithm. Japanese speakers in Japan and English speakers in both Singapore and the United States rated these words based on surface texture properties, as well as familiarity. The results show that hardness-related words were rated as harder and rougher than softness-related words, regardless of novelty and countries. Multivariate analyses of the ratings classified the hardness-related words along the hardness-softness dimension at over 80% accuracy, regardless of country. Multiple regression analyses revealed that the number of speech sounds /g/ and /k/ predicted the ratings of the surface texture properties in non-Japanese countries, suggesting a systematic relationship between phonetic features of a word and perceptual quality represented by the word across culturally and linguistically diverse samples. (shrink)

This publication presents a selection of photographic work by Hilde Honerud, made in collaboration with Yoga and Sports with Refugees (YSR) in Lesbos, Greece. It is introduced by a text coauthored with Jon Honerud. In order to engage with the experiences and the vulnerable position of the refugees involved, this project used increasingly apparent formal manipulations to convey an experience beyond the documentary image and to push observers to question the objectivity of images; to move from representation to immediate experience. (...) This entailed a kind of violence to the images that could only be done after spending a long time getting to know the organization and its context. The process raised a number of ethical questions, which we attempt to address in the text accompanying these images. The selection of images published here were part of the exhibition Reality Slipped into a Symbol, at the Vestfold Art Centre, Tonsberg, Norway (9 June–10 July 2022). (shrink)

Until a few years ago, Cognitive Science was firmly wedded to the notion that cognition must be explained in terms of the computational manipulation of internal representations or symbols. Although many people still believe this, the consensus is no longer solid. Whether it is truly threatened by connectionism is, perhaps, controversial, but there are yet more radical approaches that explicitly reject it. Advocates of "embodied" or "situated" approaches to cognition (e.g., Smith, 1991; Varela _et al_ , 1991, Clancey, 1997) (...) argue that thought cannot be understood as entirely internal. Furthermore, it is argued that autonomous robots can be designed to behave more intelligently if representationalist programming techniques are avoided (Brooks, 1991), and that the way our brains control our behavior is better understood in terms of chaos and dynamical systems theory rather than as any sort computation (e.g., Freeman & Skarda, 1990; Van Gelder & Port, 1995; Van Gelder, 1995; Garson, 1996). (shrink)

Cognitive theories based on a fixed feature set suffer from frame and symbol grounding problems. Flexible features and other empirically acquired constraints (e.g., analog-to-analog mappings) provide a framework for letting extrinsic relations influence symbol manipulation. By offering a biologically plausible basis for feature learning, nonorthogonal multiresolution analysis and dimensionality reduction, informed by functional constraints, may contribute to a solution to the symbol grounding problem.

We present a set of algorithms for automated simplification of symbolic constants of the form ∑iαixi with αi rational and xi complex. The included algorithms, called SimplifySum2 and implemented in Mathematica, remove redundant terms, attempt to make terms and the full expression real, and remove terms using repeated application of the multipair PSLQ integer relation detection algorithm. Also included are facilities for making substitutions according to user-specified identities. We illustrate this toolset by giving some real-world examples of its usage, including (...) one, for instance, where the tool reduced a symbolic expression of approximately 100 000 characters in size enough to enable manual manipulation to one with just four simple terms.2Available from https://github.com/alexkaiser/SimplifySum. (shrink)

Many scholars in recent years have focused their efforts on revealing the connection of philosophy and authority. Basically, from Nietzsche onwards, philosophyhas witnessed ongoing efforts for “will to power” by some philosophers and of course this motivated many philosophers to take part in politics. Nonetheless, thismoot point engendered a serious risk and not only contrasted with the Socratic contributions, but also paved the way for the advent of a new way of making politics where philosophy and scientific prestige are being (...) manipulated following certain interests. By comparing the US and Argentinian climates, this paper explores to what extent philosophy can and must remain independent of politics. Even though one might think of Heidegger as a clear example of this relationship, there are many other philosophers who were interested in politics and committed to political parties. One of the aspects that characterizes this new way of politics is the theatrification of reality, and philosophers are part of this process. To some extent, the prestige given to scholars for their contribution to society is being conferred to some privileged groups to gain more legitimacy, precisely in a world where the classical institutions are gradually declining. (shrink)

Quantum probability (QP) theory can be seen as a type of vector symbolic architecture (VSA): mental states are vectors storing structured information and manipulated using algebraic operations. Furthermore, the operations needed by QP match those in other VSAs. This allows existing biologically realistic neural models to be adapted to provide a mechanistic explanation of the cognitive phenomena described in the target article by Pothos & Busemeyer (P&B).

Entendemos que nenhuma sociedade constrói o presente e alicerça o futuro sem compreender sua cultura e sem conhecer o significado de sua história. O objetivo deste artigo consiste em apresentar uma metodologia aplicada na sala de aula das primeiras séries do ensino fundamental, cujo propósito foi despertar a imaginação simbólica dos alunos através do uso das lendas presentes nos livros didáticos do ensino religioso ministradas pelos docentes. Os temas estudados têm como base teórica a fenomenologia da religião, a antropologia e (...) a teoria geral do imaginário. Selecionamos para nosso estudo como fundamentação metodológica a pesquisa descritiva, de campo e a abordagem qualitativa para análise dos dados. Ponderamos que a pesquisa descritiva observa, registra, analisa e correlaciona fatos ou fenômenos sem manipulá-los, ela procura descobrir, com precisão possível, a frequência com que um fenômeno ocorre, sua relação e conexão com outros, sua natureza e característica. Nos primeiros resultados de nossa investigação cientifica foi identificado que as lendas trabalhadas na sala de aula potencializam o imaginário popular resguardando a identidade cultural de uma manifestação religiosa. Consideramos que esta metodologia de ensino proposta pode ser implantada pelos professores do ensino religioso no seu planejamento. Palavravas-chave : Lendas. Imaginação. Educação.No society is able to build the present and set the bases for the future without understanding its culture and without knowing the meaning of its history. The purpose of this article is to present the methodology put into practice in the classrooms of the first grades of the elementary school, which have the sole intention to wake up the symbolic imagination of the students through the use of the legends found in the didactic books of the religious teaching ministered by the faculty members. The topics studied are based upon the religious phenomenology, anthropology and the general theory of imaginary. For our study, we used the field research and the qualitative approach as a methodological foundation, to make the data analysis. We consider that the descriptive research observes, registers, analyses and co-relates facts or phenomena without manipulating them; such approach helps us to discover the frequency in which a phenomenon happens, the connection of the phenomenon with the others, and also its nature and characteristics. Since the first results of our scientific investigation we have identified that the legends seen by the students in their classroom have potentized the popular imaginary and have maintained the cultural identity of a religious manifestation. We consider that the teachers of religious teaching can introduce this teaching methodology proposed in their school plans. Keywords : Legends. Imagination. Education. (shrink)