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  1. Affect, behavioural schemas and the proving process.Annie Selden, John Selden & Kerry McKee - 2010 - International Journal for Mathematical Education in Science and Technology 41 (2):199-215.
    In this largely theoretical article, we discuss the relation between a kind of affect, behavioural schemas and aspects of the proving process. We begin with affect as described in the mathematics education literature, but soon narrow our focus to a particular kind of affect – nonemotional cognitive feelings. We then mention the position of feelings in consciousness because that bears on the kind of data about feelings that students can be expected to be able to report. Next we introduce the (...)
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  • Understanding mental imagery: interpretive metaphors versus explanatory models.Frederick Hayes-Roth - 1979 - Behavioral and Brain Sciences 2 (4):553-554.
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  • The “thoughtless imagery” controversy.P. N. Johnson-Laird - 1979 - Behavioral and Brain Sciences 2 (4):557-558.
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  • Neurologizing mental imagery: the physiological optics of the mind's eye.Bruce Bridgeman - 1979 - Behavioral and Brain Sciences 2 (4):550-550.
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  • A Temporal Logic for Reasoning about Processes and Plans.Drew McDermott - 1982 - Cognitive Science 6 (2):101-155.
    Much previous work in artificial intelligence has neglected representing time in all its complexity. In particular, it has neglected continuous change and the indeterminacy of the future. To rectify this, I have developed a first‐order temporal logic, in which it is possible to name and prove things about facts, events, plans, and world histories. In particular, the logic provides analyses of causality, continuous change in quantities, the persistence of facts (the frame problem), and the relationship between tasks and actions. It (...)
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  • Encapsulation and expectation.Roger Schank & Larry Hunter - 1985 - Behavioral and Brain Sciences 8 (1):29-30.
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  • Cognitive self-organization and neural modularity.Stephen Grossberg - 1985 - Behavioral and Brain Sciences 8 (1):18-19.
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  • Parallel processing explains modular informational encapsulation.Marcel Kinsbourne - 1985 - Behavioral and Brain Sciences 8 (1):23-23.
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  • The mind as a Necker Cube.Jerome Kagan - 1985 - Behavioral and Brain Sciences 8 (1):21-22.
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  • Controlled versus automatic processing.Robert J. Sternberg - 1985 - Behavioral and Brain Sciences 8 (1):32-33.
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  • On Gall's reputation and some recent “new phrenology”.C. G. Gross - 1985 - Behavioral and Brain Sciences 8 (1):16-18.
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  • Models in science and mental models in scientists and nonscientists.William F. Brewer - 2001 - Mind and Society 2 (2):33-48.
    This paper examines the form of mental representation of scientific theories in scientists and nonscientists. It concludes that images and schemas are not the appropriate form of mental representation for scientific theories but that mental models and perceptual symbols do seem appropriate for representing physical/mechanical phenomena. These forms of mental representation are postulated to have an analogical relation with the world and it is this relationship that gives them strong explanatory power. It is argued that the construct of naïve theories (...)
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  • Precis of the modularity of mind.Jerry A. Fodor - 1985 - Behavioral and Brain Sciences 8 (1):1-42.
    The Modularity of Mind proposes an alternative to the or view of cognitive architecture that has dominated several decades of cognitive science. Whereas interactionism stresses the continuity of perceptual and cognitive processes, modularity theory argues for their distinctness. It is argued, in particular, that the apparent plausibility of New Look theorizing derives from the failure to distinguish between the (correct) claim that perceptual processes are inferential and the (dubious) claim that they are unencapsidated, that is, that they are arbitrarily sensitive (...)
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  • Formal thought disorder and logical form: A symbolic computational model of terminological knowledge.Luis M. Augusto & Farshad Badie - 2022 - Journal of Knowledge Structures and Systems 3 (4):1-37.
    Although formal thought disorder (FTD) has been for long a clinical label in the assessment of some psychiatric disorders, in particular of schizophrenia, it remains a source of controversy, mostly because it is hard to say what exactly the “formal” in FTD refers to. We see anomalous processing of terminological knowledge, a core construct of human knowledge in general, behind FTD symptoms and we approach this anomaly from a strictly formal perspective. More specifically, we present here a symbolic computational model (...)
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  • Mapping the Visual Icon.Sam Clarke - 2022 - Philosophical Quarterly 72 (3):552-577.
    It is often claimed that pre-attentive vision has an ‘iconic’ format. This is seen to explain pre-attentive vision's characteristically high processing capacity and to make sense of an overlap in the mechanisms of early vision and mental imagery. But what does the iconicity of pre-attentive vision amount to? This paper considers two prominent ways of characterising pre-attentive visual icons and argues that neither is adequate: one approach renders the claim ‘pre-attentive vision is iconic’ empirically false while the other obscures its (...)
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  • When Can Making a Drawing Hinder Problem Solving? Effect of the Drawing Strategy on Linear Overgeneralizations and Problem Solving.Janina Krawitz & Stanislaw Schukajlow - 2020 - Frontiers in Psychology 11.
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  • Philosophy of Modeling: Neglected Pages of History.Karlis Podnieks - 2018 - Baltic Journal of Modern Computing 6 (3):279–303.
    The work done in the philosophy of modeling by Vaihinger (1876), Craik (1943), Rosenblueth and Wiener (1945), Apostel (1960), Minsky (1965), Klaus (1966) and Stachowiak (1973) is still almost completely neglected in the mainstream literature. However, this work seems to contain original ideas worth to be discussed. For example, the idea that diverse functions of models can be better structured as follows: in fact, models perform only a single function – they are replacing their target systems, but for different purposes. (...)
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  • Syllogistic inference.P. N. Johnson-Laird & Bruno G. Bara - 1984 - Cognition 16 (1):1-61.
    This paper reviews current psychological theories of syllogistic inference and establishes that despite their various merits they all contain deficiencies as theories of performance. It presents the results of two experiments, one using syllogisms and the other using three-term series problems, designed to elucidate how the arrangement of terms within the premises affects performance. These data are used in the construction of a theory based on the hypothesis that reasoners construct mental models of the premises, formulate informative conclusions about the (...)
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  • On Spearman's “problem of correlation”.John B. Carroll - 1985 - Behavioral and Brain Sciences 8 (1):7-7.
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  • Mental Models of the Day/Night Cycle.Stella Vosniadou & William F. Brewer - 1994 - Cognitive Science 18 (1):123-183.
    This article presents the results of an experiment which investigated elementary school children's explanations of the day/night cycle. First, third, and fifth grade children were asked to explain certain phenomena, such as the disappearance of the sun during the night, the disappearance of stars during the day, the apparent movement of the moon, and the alteration of day and night. The results showed that the majority of the children in our sample used in a consistent fashion a small number of (...)
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  • (1 other version)The philosophy of computer science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
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  • Understanding Socially Responsible Investing: The Effect of Decision Frames and Trade-off Options. [REVIEW]Katherina Glac - 2009 - Journal of Business Ethics 87 (1):41 - 55.
    Over the past two decades, the phenomenon of socially responsible investing has become more widespread. However, knowledge about the individual socially responsible investor is largely limited to descriptive and comparative accounts. The question of "why do some investors practice socially responsible investing and others don't?" is therefore still largely unanswered. To address this shortcoming in the current literature, this paper develops a model of the decision to invest socially responsibly that is grounded in the cognition literature. The hypotheses proposed in (...)
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  • The Love of Large Numbers Revisited: A Coherence Model of the Popularity Bias.Daniel W. Heck, Lukas Seiling & Arndt Bröder - 2020 - Cognition 195 (C):104069.
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  • Language as a Necessary Condition for Complex Mental Content: A Review of the Discussion on Spatial and Mathematical Thinking. [REVIEW]Arkadiusz Gut & Robert Mirski - 2018 - Roczniki Filozoficzne 66 (3):33-56.
    In this article we review the discussion over the thesis that language serves as an integrator of contents coming from different cognitive modules. After presenting the theoretical considerations, we examine two strands of empirical research that tested the hypothesis — spatial cognition and mathematical cognition. The idea shared by both of them is that each is composed of two separate modules processing information of a specific kind. For spatial thinking these are geometric information about the location of the object and (...)
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  • The Science of Conceptual Systems: A Progress Report.Steven E. Wallis - 2016 - Foundations of Science 21 (4):579-602.
    In this paper I provide a brief history of the emerging science of conceptual systems, explain some methodologies, their sources of data, and the understandings that they have generated. I also provide suggestions for extending the science-based research in a variety of directions. Essentially, I am opening a conversation that asks how this line of research might be extended to gain new insights—and eventually develop more useful and generally accepted methods for creating and evaluating theory. This effort will support our (...)
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  • Digit memory of grand experts in abacus-derived mental calculation.Giyoo Hatano & Keiko Osawa - 1983 - Cognition 15 (1-3):95-110.
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  • The imprecision of mental imagery.Thomas P. Moran - 1979 - Behavioral and Brain Sciences 2 (4):560-560.
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  • On interpretative processes in imagery.Manuel de Vega - 1979 - Behavioral and Brain Sciences 2 (4):551-551.
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  • Faculties, modules, and computers.Daniel N. Robinson - 1985 - Behavioral and Brain Sciences 8 (1):28-29.
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  • Qualitative Models in Computational Simulative Sciences: Representation, Confirmation, Experimentation.Nicola Angius - 2019 - Minds and Machines 29 (3):397-416.
    The Epistemology Of Computer Simulation has developed as an epistemological and methodological analysis of simulative sciences using quantitative computational models to represent and predict empirical phenomena of interest. In this paper, Executable Cell Biology and Agent-Based Modelling are examined to show how one may take advantage of qualitative computational models to evaluate reachability properties of reactive systems. In contrast to the thesis, advanced by EOCS, that computational models are not adequate representations of the simulated empirical systems, it is shown how (...)
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  • (1 other version)What is Sustainable Theory? A Luhmannian Perspective on the Science of Conceptual Systems.Vladislav Valentinov & Steven E. Wallis - 2017 - Foundations of Science 22 (4):733-747.
    Sustainability is an important topic for understanding and developing our society. For scholars who want their academic contributions to have an impact, sustainability is important for our conceptual systems. Because our conceptual systems share similarities with our social systems, we may investigate their characteristics to gain insight into how both may be achieved or at least understood. Theories of the humanities as well as the social/behavioral sciences are changing very rapidly. They are fragile and few seem to have any longevity. (...)
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  • (2 other versions)Capturing the scientific imagination.Fiora Salis & Roman Frigg - 2019 - In Arnon Levy & Peter Godfrey-Smith (eds.), The Scientific Imagination. New York, US: Oup Usa.
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  • The demands of mental travel: demand characteristics of mental imagery experiments.Charles L. Richman, David B. Mitchell & J. Steven Reznick - 1979 - Behavioral and Brain Sciences 2 (4):564-565.
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  • A Social‐Cognitive Framework of Multidisciplinary Team Innovation.Susannah B. F. Paletz & Christian D. Schunn - 2010 - Topics in Cognitive Science 2 (1):73-95.
    The psychology of science typically lacks integration between cognitive and social variables. We present a new framework of team innovation in multidisciplinary science and engineering groups that ties factors from both literatures together. We focus on the effects of a particularly challenging social factor, knowledge diversity, which has a history of mixed effects on creativity, most likely because those effects are mediated and moderated by cognitive and additional social variables. In addition, we highlight the distinction between team innovative processes that (...)
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  • The Role of Evaluation-Driven Rejection in the Successful Exploration of a Conceptual Space of Stories.Carlos León & Pablo Gervás - 2010 - Minds and Machines 20 (4):615-634.
    Evaluation processes are a basic component of creativity. They guide not only the pure judgement about a new artefact but also the generation itself, as creators constantly evaluate their own work. This paper proposes a model for automatic story generation based on the evaluation of stories. A model of how quality in stories is evaluated is presented, and two possible implementations of the generation guided by this evaluation are shown: exhaustive space exploration and constrained exploration. A theoretical model and its (...)
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  • The image-like and the language-like.Benny Shanon - 1979 - Behavioral and Brain Sciences 2 (4):566-567.
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  • Images, memory, and perception.Alastair Hannay - 1979 - Behavioral and Brain Sciences 2 (4):552-553.
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  • Naturalistic Cognition: A Research Paradigm for Human-Centered Design.Peter Storkerson - 2010 - Journal of Research Practice 6 (2):Article M12.
    Naturalistic thinking and knowing, the tacit, experiential, and intuitive reasoning of everyday interaction, have long been regarded as inferior to formal reason and labeled primitive, fallible, subjective, superstitious, and in some cases ineffable. But, naturalistic thinking is more rational and definable than it appears. It is also relevant to design. Inquiry into the mechanisms of naturalistic thinking and knowledge can bring its resources into focus and enable designers to create better, human-centered designs for use in real-world settings. This article makes (...)
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  • Combe's crucible and the music of the modules.John C. Marshall - 1985 - Behavioral and Brain Sciences 8 (1):23-24.
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  • A neo-Cartesian alternative.David Caplan - 1985 - Behavioral and Brain Sciences 8 (1):6-7.
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  • Vertically unparalleled.Ignatius G. Mattingly & Alvin M. Liberman - 1985 - Behavioral and Brain Sciences 8 (1):24-26.
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  • A rapprochement of biology, psychology, and philosophy.Sandra Scarr - 1985 - Behavioral and Brain Sciences 8 (1):29-29.
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  • Framing-effects approach: A theoretical and methodological critique.Bertram Scheufele - 2004 - Communications 29 (4):401-428.
    The article deals with research on framing effects. First, I will start with classifying different approaches on framing. Subsequently, I will provide a definition of the concepts of frame, schema and framing, expand on framing research conducted so far – both theoretically and operationally. Having this equipment at hand, I will initiate a discussion on studies of framing-effects in terms of theory, methods and empirical results. This discussion leads to the conclusion that studies on framing effects are insufficiently concerned with (...)
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  • Inference during reading.Gail McKoon & Roger Ratcliff - 1992 - Psychological Review 99 (3):440-466.
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  • A decision network account of reasoning about other people’s choices.Alan Jern & Charles Kemp - 2015 - Cognition 142 (C):12-38.
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  • The modularity of behavior.Peter R. Killeen - 1985 - Behavioral and Brain Sciences 8 (1):22-23.
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  • Imagery without arrays.Geoffrey Hinton - 1979 - Behavioral and Brain Sciences 2 (4):555-556.
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  • Emergence of scientific understanding in real-time ecological research practice.Luana Poliseli - 2020 - History and Philosophy of the Life Sciences 42 (4):1-25.
    Scientific understanding as a subject of inquiry has become widely discussed in philosophy of science and is often addressed through case studies from history of science. Even though these historical reconstructions engage with details of scientific practice, they usually provide only limited information about the gradual formation of understanding in ongoing processes of model and theory construction. Based on a qualitative ethnographic study of an ecological research project, this article shifts attention from understanding in the context of historical case studies (...)
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  • Uses of cognitive science to science education.W. Jung - 1993 - Science & Education 2 (1):31-56.
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  • What's wrong with story grammars.Alan Garnham - 1983 - Cognition 15 (1-3):145-154.
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