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  1. The Cognitive Ecology of the Internet.Paul Smart, Richard Heersmink & Robert Clowes - 2017 - In Stephen Cowley & Frederic Vallée-Tourangeau (eds.), Cognition Beyond the Brain: Computation, Interactivity and Human Artifice (2nd ed.). Springer. pp. 251-282.
    In this chapter, we analyze the relationships between the Internet and its users in terms of situated cognition theory. We first argue that the Internet is a new kind of cognitive ecology, providing almost constant access to a vast amount of digital information that is increasingly more integrated into our cognitive routines. We then briefly introduce situated cognition theory and its species of embedded, embodied, extended, distributed and collective cognition. Having thus set the stage, we begin by taking an embedded (...)
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  • The cognitive integration of scientific instruments: Information, situated cognition, and scientific practice.Richard Heersmink - 2016 - Phenomenology and the Cognitive Sciences 15 (4):1-21.
    Researchers in the biological and biomedical sciences, particularly those working in laboratories, use a variety of artifacts to help them perform their cognitive tasks. This paper analyses the relationship between researchers and cognitive artifacts in terms of integration. It first distinguishes different categories of cognitive artifacts used in biological practice on the basis of their informational properties. This results in a novel classification of scientific instruments, conducive to an analysis of the cognitive interactions between researchers and artifacts. It then uses (...)
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  • Building Cognition: The Construction of Computational Representations for Scientific Discovery.Sanjay Chandrasekharan & Nancy J. Nersessian - 2015 - Cognitive Science 39 (8):1727-1763.
    Novel computational representations, such as simulation models of complex systems and video games for scientific discovery, are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that (...)
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  • Situating distributed cognition.Lisa M. Osbeck & Nancy J. Nersessian - 2014 - Philosophical Psychology 27 (1):1-16.
    We historically and conceptually situate distributed cognition by drawing attention to important similarities in assumptions and methods with those of American ?functional psychology? as it emerged in contrast and complement to controlled laboratory study of the structural components and primitive ?elements? of consciousness. Functional psychology foregrounded the adaptive features of cognitive processes in environments, and adopted as a unit of analysis the overall situation of organism and environment. A methodological implication of this emphasis was, to the extent possible, the study (...)
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  • Explanatory anti-psychologism overturned by lay and scientific case classifications.Jonathan Waskan, Ian Harmon, Zachary Horne, Joseph Spino & John Clevenger - 2014 - Synthese 191 (5):1-23.
    Many philosophers of science follow Hempel in embracing both substantive and methodological anti-psychologism regarding the study of explanation. The former thesis denies that explanations are constituted by psychological events, and the latter denies that psychological research can contribute much to the philosophical investigation of the nature of explanation. Substantive anti-psychologism is commonly defended by citing cases, such as hyper-complex descriptions or vast computer simulations, which are reputedly generally agreed to constitute explanations but which defy human comprehension and, as a result, (...)
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  • Affective problem solving: emotion in research practice.Lisa M. Osbeck & Nancy J. Nersessian - 2011 - Mind and Society 10 (1):57-78.
    This paper presents an analysis of emotional and affectively toned discourse in biomedical engineering researchers’ accounts of their problem solving practices. Drawing from our interviews with scientists in two laboratories, we examine three classes of expression: explicit, figurative and metaphorical, and attributions of emotion to objects and artifacts important to laboratory practice. We consider the overall function of expressions in the particular problem solving contexts described. We argue that affective processes are engaged in problem solving, not as simply tacked onto (...)
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  • Interdisciplinarity in the Making: Models and Methods in Frontier Science.Nancy J. Nersessian - 2022 - Cambridge, MA: MIT.
    A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...)
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  • Rethinking Ethnography for Philosophy of Science.Nancy J. Nersessian & Miles MacLeod - 2022 - Philosophy of Science 89 (4):721-741.
    We lay groundwork for applying ethnographic methods in philosophy of science. We frame our analysis in terms of two tasks: to identify the benefits of an ethnographic approach in philosophy of science and to structure an ethnographic approach for philosophical investigation best adapted to provide information relevant to philosophical interests and epistemic values. To this end, we advocate for a purpose-guided form of cognitive ethnography that mediates between the explanatory and normative interests of philosophy of science, while maintaining openness and (...)
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  • The role of disciplinary perspectives in an epistemology of scientific models.Mieke Boon - 2020 - European Journal for Philosophy of Science 10 (3):1-34.
    The purpose of this article is to develop an epistemology of scientific models in scientific research practices, and to show that disciplinary perspectives have crucial role in such an epistemology. A transcendental approach is taken, aimed at explanations of the kinds of questions relevant to the intended epistemology, such as “How is it possible that models provide knowledge about aspects of reality?” The approach is also pragmatic in the sense that the questions and explanations must be adequate and relevant to (...)
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  • Interdisciplinarities in Action: Cognitive Ethnography of Bioengineering Sciences Research Laboratories.Nancy J. Nersessian - 2019 - Perspectives on Science 27 (4):553-581.
    The paper frames interdisciplinary research as creating complex, distributed cognitive-cultural systems. It introduces and elaborates on the method of cognitive ethnography as a primary means for investigating interdisciplinary cognitive and learning practices in situ. The analysis draws from findings of nearly 20 years of investigating such practices in research laboratories in pioneering bioengineering sciences. It examines goals and challenges of two quite different kinds of integrative problem-solving practices: biomedical engineering (hybridization) and integrative systems biology (collaborative interdependence). Practical lessons for facilitating (...)
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  • Domain-Creating Constraints.Robert L. Goldstone & David Landy - 2010 - Cognitive Science 34 (7):1357-1377.
    The contributions to this special issue on cognitive development collectively propose ways in which learning involves developing constraints that shape subsequent learning. A learning system must be constrained to learn efficiently, but some of these constraints are themselves learnable. To know how something will behave, a learner must know what kind of thing it is. Although this has led previous researchers to argue for domain-specific constraints that are tied to different kinds/domains, an exciting possibility is that kinds/domains themselves can be (...)
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  • Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.Miles MacLeod & Nancy J. Nersessian - 2018 - History and Philosophy of the Life Sciences 40 (1):17.
    Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...)
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  • The Feasibility of Folk Science.Frank C. Keil - 2010 - Cognitive Science 34 (5):826-862.
    If folk science means individuals having well worked out mechanistic theories of the workings of the world, then it is not feasible. Laypeople’s explanatory understandings are remarkably coarse, full of gaps, and often full of inconsistencies. Even worse, most people overestimate their own understandings. Yet recent views suggest that formal scientists may not be so different. In spite of these limitations, science somehow works and its success offers hope for the feasibility of folk science as well. The success of science (...)
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  • Beauty in experiment: A qualitative analysis of aesthetic experiences in scientific practice.Milena Ivanova, Bridget Ritz, Marcela Duque & Brandon Vaidyanathan - 2024 - Studies in History and Philosophy of Science Part A 104 (C):3-11.
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  • Coupling simulation and experiment: The bimodal strategy in integrative systems biology.Miles MacLeod & Nancy J. Nersessian - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4a):572-584.
    The importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and cell-signaling (...)
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  • Epistemological and educational issues in teaching practice-oriented scientific research: roles for philosophers of science.Mieke Boon, Mariana Orozco & Kishore Sivakumar - 2022 - European Journal for Philosophy of Science 12 (1):1-23.
    The complex societal challenges of the twenty-first Century require scientific researchers and academically educated professionals capable of conducting scientific research in complex problem contexts. Our central claim is that educational approaches inspired by a traditional empiricist epistemology insufficiently foster the required deep conceptual understanding and higher-order thinking skills necessary for epistemic tasks in scientific research. Conversely, we argue that constructivist epistemologies provide better guidance to educational approaches to promote research skills. We also argue that teachers adopting a constructivist learning theory (...)
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  • Rethinking correspondence: how the process of constructing models leads to discoveries and transfer in the bioengineering sciences.Nancy J. Nersessian & Sanjay Chandrasekharan - 2017 - Synthese 198 (Suppl 21):1-30.
    Building computational models of engineered exemplars, or prototypes, is a common practice in the bioengineering sciences. Computational models in this domain are often built in a patchwork fashion, drawing on data and bits of theory from many different domains, and in tandem with actual physical models, as the key objective is to engineer these prototypes of natural phenomena. Interestingly, such patchy model building, often combined with visualizations, whose format is open to a wide range of choice, leads to the discovery (...)
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  • Mesoscopic modeling as a cognitive strategy for handling complex biological systems.Miles MacLeod & Nancy J. Nersessian - 2019 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 78:101201.
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