10,308 research outputs found

    The Case for Dynamic Models of Learners' Ontologies in Physics

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    In a series of well-known papers, Chi and Slotta (Chi, 1992; Chi & Slotta, 1993; Chi, Slotta & de Leeuw, 1994; Slotta, Chi & Joram, 1995; Chi, 2005; Slotta & Chi, 2006) have contended that a reason for students' difficulties in learning physics is that they think about concepts as things rather than as processes, and that there is a significant barrier between these two ontological categories. We contest this view, arguing that expert and novice reasoning often and productively traverses ontological categories. We cite examples from everyday, classroom, and professional contexts to illustrate this. We agree with Chi and Slotta that instruction should attend to learners' ontologies; but we find these ontologies are better understood as dynamic and context-dependent, rather than as static constraints. To promote one ontological description in physics instruction, as suggested by Slotta and Chi, could undermine novices' access to productive cognitive resources they bring to their studies and inhibit their transition to the dynamic ontological flexibility required of experts.Comment: The Journal of the Learning Sciences (In Press

    Semantic form as interface

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    The term interface had a remarkable career over the past several decades, motivated largely by its use in computer science. Although the concept of a "surface common to two areas" (Oxford Advanced Learner's Dictionary, 1980) is intuitively clear enough, the range of its application is not very sharp and well defined, a "common surface" is open to a wide range of interpretations

    Whatever Happened to Evans' Action Component?

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    A long line of writers on Evans – Andy Hamilton, Lucy O'Brien, Jose Bermudez, and Jason Stanley, to name just a few – assess Evans' account of first-person thought without heeding his warnings that his theory comprises an information and an action component. By omitting the action component, these critics are able to characterize Evans' theory as a perceptual model theory and reject it on that ground. This paper is an attempt to restore the forgotten element. With this component put back in, the charge of Evans' theory as a perceptual model of such thoughts falls apart, and the theory turns out to have enough merit to project itself as a legitimate contender for a plausible account of 'I'-thought

    Semantic networks

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    AbstractA semantic network is a graph of the structure of meaning. This article introduces semantic network systems and their importance in Artificial Intelligence, followed by I. the early background; II. a summary of the basic ideas and issues including link types, frame systems, case relations, link valence, abstraction, inheritance hierarchies and logic extensions; and III. a survey of ‘world-structuring’ systems including ontologies, causal link models, continuous models, relevance, formal dictionaries, semantic primitives and intersecting inference hierarchies. Speed and practical implementation are briefly discussed. The conclusion argues for a synthesis of relational graph theory, graph-grammar theory and order theory based on semantic primitives and multiple intersecting inference hierarchies

    What to Read: A Biased Guide to AI Literacy for the Beginner

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    Acknowledgements. It was Ken Forbus' idea, and he, Howie Shrobe, Dan Weld, and John Batali read various drafts. Dan Huttenlocher and Tom Knight helped with the speech recognition section. The science fiction section was prepared with the aid of my SF/AI editorial board, consisting of Carl Feynman and David Wallace, and of the ArpaNet SF-Lovers community. Even so, all responsibility rests with me.This note tries to provide a quick guide to AI literacy for the beginning AI hacker and for the experienced AI hacker or two whose scholarship isn't what it should be. most will recognize it as the same old list of classic papers, give or take a few that I feel to be under- or over-rated. It is not guaranteed to be thorough or balanced or anything like that.MIT Artificial Intelligence Laborator

    Topological Foundations of Cognitive Science

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    A collection of papers presented at the First International Summer Institute in Cognitive Science, University at Buffalo, July 1994, including the following papers: ** Topological Foundations of Cognitive Science, Barry Smith ** The Bounds of Axiomatisation, Graham White ** Rethinking Boundaries, Wojciech Zelaniec ** Sheaf Mereology and Space Cognition, Jean Petitot ** A Mereotopological Definition of 'Point', Carola Eschenbach ** Discreteness, Finiteness, and the Structure of Topological Spaces, Christopher Habel ** Mass Reference and the Geometry of Solids, Almerindo E. Ojeda ** Defining a 'Doughnut' Made Difficult, N .M. Gotts ** A Theory of Spatial Regions with Indeterminate Boundaries, A.G. Cohn and N.M. Gotts ** Mereotopological Construction of Time from Events, Fabio Pianesi and Achille C. Varzi ** Computational Mereology: A Study of Part-of Relations for Multi-media Indexing, Wlodek Zadrozny and Michelle Ki

    Abstract Concepts: Sensory-Motor Grounding, Metaphors, and Beyond

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    Abstract In the last decade many researchers have obtained evidence for the idea that cognition shares processing mechanisms with perception and action. Most of the evidence supporting the grounded cognition framework focused on representations of concrete concepts, which leaves open the question how abstract concepts are grounded in sensory-motor processing. One promising idea is that people simulate concrete situations and introspective experiences to represent abstract concepts [Barsalou, L. W., & Wiemer-Hastings, K. (2005). Situating abstract concepts. In D. Pecher, & R. A. Zwaan (Eds.), Grounding cognition: The role of perception and action in memory, language, and thinking (pp. 129–163). Cambridge: Cambridge University Press.], although this has not yet been investigated a lot. A second idea, which more researchers have investigated, is that people use metaphorical mappings from concrete to abstract concepts [Lakoff, G., & Johnson, M. (1980). Metaphors we live by. Chicago: Chicago University Press.]. According to this conceptual metaphor theory, image schemas structure and provide sensory-motor grounding for abstract concepts. Although there is evidence that people automatically activate image schemas when they process abstract concepts, we argue that situations are also needed to fully represent meaning
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