56,424 research outputs found

    Models, Modelling, Metaphors and Metaphorical Thinking - From an Educational Philosophical View

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    In this contribution, I present my view of models and metaphors within educational research, very broadly speaking. I start out by articulating my educational philosophical perspective as a form of applied philosophy. Inspired by RicƓur, I then define models as “instruments for configuration and reconfiguration”. I argue that metaphors and metaphorical thinking are more basic than models and modelling. The former can guide reasoning in a holistic, heuristic manner. The latter can be used analytically to develop the initial metaphorical similarity into articulated analogies. Models and metaphors may be deployed explicitly and consciously but may also (mis)lead cognition through implicit structuring of thinking. I proceed to give examples of the roles which models and metaphors have within different areas of (research in) education, teaching, and learning. One example is the explicit development of design patterns; another is implicit adherence to either an acquisition metaphor or a participation metaphor of learning. Towards the end, I provide tentative answers to three questions posed by my discussion pair, Willard McCarty, concerning 1) computer modelling, 2) open-endedness of models and metaphors, and 3) situated knowledge and relativism

    Music, discourse and intuitive technology

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    This paper proposes that intuitive technologies play a vital role in cognition and cultural reception. The case of music is considered in particular. The perceived temporality of contemporary technology is shown to be an artificial barrier to the acknowledgement of longer-term dynamics. The increased role of explanatory metaphors from technology is traced across various fields of study. Processes of sense-making – conscious or otherwise – are seen as an informal, unreflected repertory of mechanisms ranging from predictive models to instrumental metaphors. It is suggested that these derive by assimilation and induction from the technological milieu within which the subject develops and operates. The acquisition of these models and metaphors is itself an imaginative process, based on experience ranging from partial expertise to fantastical extrapolation

    Mind: meet network. Emergence of features in conceptual metaphor.

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    As a human product, language reflects the psychological experience of man (Radden and Dirven, 2007). One model of language and human cognition in general is connectionism, by many linguists is regarded as mathematical and, therefore, too reductive. This opinion trend seems to be reversing, however, due to the fact that many cognitive researchers begin to appreciate one attribute of network models: feature emergence. In the course of a network simulation properties emerge that were neither inbuilt nor intended by its creators (Elman, 1998), in other words, the whole becomes more than just the sum of its parts. Insight is not only drawn from the network's output, but also the means that the network utilizes to arrive at the output.\ud It may seem obvious that the events of life should be meaningful for human beings, yet there is no widely accepted theory as to how do we derive that meaning. The most promising hypothesis regarding the question how the world is meaningful to us is that of embodied cognition (cf. Turner 2009), which postulates that the functions of the brain evolved so as to ‘understand’ the body, thus grounding the mind in an experiential foundation. Yet, the relationship between the body and the mind is far from perspicuous, as research insight is still intertwined with metaphors specific for the researcher’s methodology (Eliasmith 2003). It is the aim of this paper to investigate the conceptual metaphor in a manner that will provide some insight with regard to the role that objectification, as defined by Szwedek (2002), plays in human cognition and identify one possible consequence of embodied cognition.\ud If the mechanism for concept formation, or categorization of the world, resembles a network, it is reasonable to assume that evidence for this is to be sought in language. Let us then postulate the existence of a network mechanism for categorization and concept formation present in the human mind and initially developed to cope with the world directly accessible to the early human (i.e. tangible). Such a network would convert external inputs to form an internal, multi modal representation of a perceived object in the brain. The sheer amount of available information and the computational restrictions of the brain would force some sort of data compression, or a computational funnel. It has been shown that a visual perception network of this kind can learn to accurately label patterns (Elman, 1998). What is more, the compression of data facilitated the recognition of prototypes of a given pattern category rather than its peripheral representations, an emergent property that supports the prototype theory of the mental lexicon (cf. Radden and Dirven, 2007).\ud The present project proposes that, in the domain of cognition, the process of objectification, as defined by Szwedek (2002), would be an emergent property of such a system, or that if an abstract notion is computed by a neural network designed to cope with tangible concepts the data compression mechanism would require the notion to be conceptualized as an object to permit further processing. The notion of emergence of meaning from the operation of complex systems is recognised as an important process in a number of studies on metaphor comprehension. Feature emergence is said to occur when a non-salient feature of the target and the vehicle becomes highly salient in the metaphor (Utsumi 2005). Therefore, for example, should objectification emerge as a feature in the metaphor KNOWLEDGE IS A TREASURE, the metaphor would be characterised as having more\ud features of an object than either the target or vehicle alone. This paper focuses on providing a theoretical connectionist network based on the Elman-type network (Elman, 1998) as a model of concept formation where objectification would be an emergent feature. This is followed by a psychological experiment whereby the validity of this assumption is tested through a questionnaire where two groups of participants are asked to evaluate either metaphors or their components. The model proposes an underlying relation between the mechanism for concept formation and the omnipresence of conceptual metaphors, which are interpreted as resulting from the properties of the proposed network system.\ud Thus, an evolutionary neural mechanism is proposed for categorization of the world, that is able to cope with both concrete and abstract notions and the by-product of which are the abstract language-related phenomena, i.e. metaphors. The model presented in this paper aims at providing a unified account of how the various types of phenomena, objects, feelings etc. are categorized in the human mind, drawing on evidence from language.\ud References:\ud Szwedek, Aleksander. 2002. Objectification: From Object Perception To Metaphor Creation. In B. Lewandowska-Tomaszczyk and K. Turewicz (eds). Cognitive Linguistics To-day, 159-175. Frankfurt am Main: Peter Lang.\ud Radden, GĂŒnter and Dirven, RenĂ©. 2007. Cognitive English Grammar. Amsterdam/ Philadelphia: John Benjamins Publishing Company\ud Eliasmith, Chris. 2003. Moving beyond metaphors: understanding the mind for what it is. Journal of Philosophy. C(10):493- 520.\ud Elman, J. L. et al. 1998. Rethinking innateness: A connectionist perspective on development. Cambridge, MA: MIT Press\ud Turner, Mark. 2009. Categorization of Time and Space Through Language. (Paper presented at the FOCUS2009 conference "Categorization of the world through language". Serock, 25-28 February 2009).\ud Utsumi, Akira. 2005. The role of feature emergence in metaphor appreciation, Metaphor and Symbol, 20(3), 151-172

    Contextual Effects on Metaphor Comprehension: Experiment and Simulation

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    This paper presents a computational model of referential metaphor comprehension. This model is designed on top of Latent Semantic Analysis (LSA), a model of the representation of word and text meanings. Compre­hending a referential metaphor consists in scanning the semantic neighbors of the metaphor in order to find words that are also semantically related to the context. The depth of that search is compared to the time it takes for humans to process a metaphor. In particular, we are interested in two independent variables : the nature of the reference (either a literal meaning or a figurative meaning) and the nature of the context (inductive or not inductive). We show that, for both humans and model, first, metaphors take longer to process than the literal meanings and second, an inductive context can shorten the processing time

    Language as a disruptive technology: Abstract concepts, embodiment and the flexible mind

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    A growing body of evidence suggests that cognition is embodied and grounded. Abstract concepts, though, remain a significant theoretical chal- lenge. A number of researchers have proposed that language makes an important contribution to our capacity to acquire and employ concepts, particularly abstract ones. In this essay, I critically examine this suggestion and ultimately defend a version of it. I argue that a successful account of how language augments cognition should emphasize its symbolic properties and incorporate a view of embodiment that recognizes the flexible, multi- modal and task-related nature of action, emotion and perception systems. On this view, language is an ontogenetically disruptive cognitive technology that expands our conceptual reach
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