Cognition In The Wild
01 Jan 2016-
TL;DR: The cognition in the wild is universally compatible with any devices to read and is available in the digital library an online access to it is set as public so you can download it instantly.
Abstract: Thank you very much for reading cognition in the wild. Maybe you have knowledge that, people have look hundreds times for their favorite books like this cognition in the wild, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. cognition in the wild is available in our digital library an online access to it is set as public so you can download it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the cognition in the wild is universally compatible with any devices to read.
Citations
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TL;DR: Evidence is described that a major component of proficiency at algebraic reasoning is Rigged Up Perception-Action Systems (RUPAS), via which originally demanding, strategically controlled cognitive tasks are converted into learned, automatically executed perception and action routines.
Abstract: Formal mathematical reasoning provides an illuminating test case for understanding how humans can think about things that they did not evolve to comprehend. People engage in algebraic reasoning by ...
29 citations
Cites background from "Cognition In The Wild"
...Well-designed tools can turn error-prone conceptual tasks into robust perceptual ones (Hutchins, 1995)....
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TL;DR: In this paper, the authors introduce a three-layered model of information in cities, namely environmental information in physical space, information in semantic space, and the information enacted by interacting agents, and apply these measures to emblematic urban cases and simulated scenarios.
Abstract: From physics to the social sciences, information is now seen as a fundamental component of reality. However, a form of information seems still underestimated, perhaps precisely because it is so pervasive that we take it for granted: the information encoded in the very environment we live in. We still do not fully understand how information takes the form of cities, and how our minds deal with it in order to learn about the world, make daily decisions, and take part in the complex system of interactions we create as we live together. This paper addresses three related problems that need to be solved if we are to understand the role of environmental information: (1) the physical problem: how can we preserve information in the built environment? (2) The semantic problem: how do we make environmental information meaningful? and (3) the pragmatic problem: how do we use environmental information in our daily lives? Attempting to devise a solution to these problems, we introduce a three-layered model of information in cities, namely environmental information in physical space, environmental information in semantic space, and the information enacted by interacting agents. We propose forms of estimating entropy in these different layers, and apply these measures to emblematic urban cases and simulated scenarios. Our results suggest that ordered spatial structures and diverse land use patterns encode information, and that aspects of physical and semantic information affect coordination in interaction systems.
28 citations
TL;DR: There are (at least) two ways to think of the differences in basic concepts and typologies that one can find in different scientific practices that constitute a research tradition as discussed by the authors, and one is the f...
Abstract: There are (at least) two ways to think of the differences in basic concepts and typologies that one can find in the different scientific practices that constitute a research tradition. One is the f...
28 citations
Cites background from "Cognition In The Wild"
...This is precisely the sense in which Hutchins (1995) uses the term, for example, when referring to scaffolding as what makes the learning of the practice of “standard steaming watch” easier....
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...He claims that “the scaffolding provided to the novice by the other members of the team is constructed on cultural understandings about what is hard and what is easy to learn” (Hutchins, 1995, p. 280)....
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TL;DR: This article uses quantitative methods to evaluate Zooniverse, the world’s largest citizen science web portal, and calls for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research.
Abstract: Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world's largest citizen science web portal. We use quantitative methods to evaluate the platform's success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how information and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research.
28 citations
Cites background from "Cognition In The Wild"
...Crowdsourcing is hardly the only activity in which this kind of heterogeneous connectivity is evident (Hutchins 1995; Cetina 1999; Latour 2005), but it does pose a vivid example of how large groups come together to forge scientific knowledge....
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Posted Content•
TL;DR: In this paper, the concept of Enabling Spaces is introduced as a space that is designed in such a way that it enables and facilitates processes of collaborative knowledge creation and innovation, and a case for an Enabling Space which functions as a collaborative innovation network.
Abstract: As opposed to managing or controlling innovation processes, this paper proposes the notion of enabling as a more suitable approach to innovation. As a consequence, the concept of Enabling Spaces is introduced as a space that is designed in such a way that it enables and facilitates processes of collaborative knowledge creation and innovation. In that context a rather broad notion of space is applied: It goes far beyond architectural/physical space by integrating social, cognitive, emotional, organizational, and epistemological dimensions in an interdisciplinary manner. Both the theoretical background and the methodological approach and design process will be presented. Furthermore, we will discuss a case for an Enabling Space which functions as a collaborative innovation network. It will turn out that Enabling Spaces and Collaborative Innovation Networks (COINs) share a lot of characteristics, attitudes, and values.
28 citations
References
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TL;DR: The authors argue that the affordances an environment offers to an animal are dependent on the skills the animal possesses and that the landscape of affordances we inhabit as humans is very rich and resourceful.
Abstract: How broad is the class of affordances we can perceive? Affordances (Gibson, 1979/1986) are possibilities for action provided to an animal by the environment—by the substances, surfaces, objects, and other living creatures that surround it. A widespread assumption has been that affordances primarily relate to motor action—to locomotion and manual behaviors such as reaching and grasping. We propose an account of affordances according to which the concept of affordances has a much broader application than has hitherto been supposed. We argue that the affordances an environment offers to an animal are dependent on the skills the animal possesses. By virtue of our many abilities, the landscape of affordances we inhabit as humans is very rich and resourceful.
628 citations
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TL;DR: Situative analyses include hypotheses about principles of coordination that support communication and reasoning in activity systems, including construction of meaning and understanding as discussed by the authors, which is a program of research in the learning sciences that I call "situative".
Abstract: This chapter discusses a program of research in the learning sciences that I call “situative.” The defining characteristic of a situative approach is that instead of focusing on individual learners, the main focus of analysis is on activity systems : complex social organizations containing learners, teachers, curriculum materials, software tools, and the physical environment. Over the decades, many psychologists have advocated a study of these larger systems (Dewey, 1896, 1929/1958; Lewin, 1935, 1946/1997; Mead, 1934; Vygotsky, 1987), although they remained outside the mainstream of psychology, which instead focused on individuals. Situative analyses include hypotheses about principles of coordination that support communication and reasoning in activity systems, including construction of meaning and understanding. Other terms for the perspective I refer to as situative include sociocultural psychology (Cole, 1996; Rogoff, 1995), activity theory (Engestrom, 1993; 1999), distributed cognition (Hutchins, 1995a), and ecological psychology (Gibson, 1979; Reed, 1996). I use the term “situative” because I was introduced to the perspective by scholars who referred to their perspective as situated action (Suchman, 1985), situated cognition (Lave, 1988), or situated learning (Lave & Wenger, 1991). I prefer the term “situative,” a modifier of “perspective,” “analysis,” or “theory,” to “situated,” used to modify “action,” “cognition,” or “learning,” because the latter adjective invites a misconception: that some instances of action, cognition, or learning are situated and others are not. During the 1980s and 1990s these scholars and others provided analyses in which concepts of cognition and learning are relocated at the level of activity systems.
545 citations
TL;DR: This work argues that advances in digital technologies increase innovation network connectivity by reducing communication costs and increasing its reach and scope and increase the speed and scope of digital convergence, which increases network knowledge heterogeneity and need for integration.
Abstract: The increased digitization of organizational processes and products poses new challenges for understanding product innovation. It also opens new horizons for information systems research. We analyse how ongoing pervasive digitization of product innovation reshapes knowledge creation and sharing in innovation networks. We argue that advances in digital technologies 1 increase innovation network connectivity by reducing communication costs and increasing its reach and scope and 2 increase the speed and scope of digital convergence, which increases network knowledge heterogeneity and need for integration. These developments, in turn, stretch existing innovation networks by redistributing control and increasing the demand for knowledge coordination across time and space presenting novel challenges for knowledge creation, assimilation and integration. Based on this foundation, we distinguish four types of emerging innovation networks supported by digitalization: 1 project innovation networks; 2 clan innovation networks; 3 federated innovation networks; and 4 anarchic innovation networks. Each network involves different cognitive and social translations - or ways of identifying, sharing and assimilating knowledge. We describe the role of five novel properties of digital infrastructures in supporting each type of innovation network: representational flexibility, semantic coherence, temporal and spatial traceability, knowledge brokering and linguistic calibration. We identify several implications for future innovation research. In particular, we focus on the emergence of anarchic network forms that follow full-fledged digital convergence founded on richer innovation ontologies and epistemologies calling to critically re-examine the nature and impact of modularization for innovation.
418 citations
TL;DR: A blind IQA model is proposed, which learns qualitative evaluations directly and outputs numerical scores for general utilization and fair comparison and is not only much more natural than the regression-based models, but also robust to the small sample size problem.
Abstract: This paper investigates how to blindly evaluate the visual quality of an image by learning rules from linguistic descriptions. Extensive psychological evidence shows that humans prefer to conduct evaluations qualitatively rather than numerically. The qualitative evaluations are then converted into the numerical scores to fairly benchmark objective image quality assessment (IQA) metrics. Recently, lots of learning-based IQA models are proposed by analyzing the mapping from the images to numerical ratings. However, the learnt mapping can hardly be accurate enough because some information has been lost in such an irreversible conversion from the linguistic descriptions to numerical scores. In this paper, we propose a blind IQA model, which learns qualitative evaluations directly and outputs numerical scores for general utilization and fair comparison. Images are represented by natural scene statistics features. A discriminative deep model is trained to classify the features into five grades, corresponding to five explicit mental concepts, i.e., excellent, good, fair, poor, and bad. A newly designed quality pooling is then applied to convert the qualitative labels into scores. The classification framework is not only much more natural than the regression-based models, but also robust to the small sample size problem. Thorough experiments are conducted on popular databases to verify the model’s effectiveness, efficiency, and robustness.
360 citations
TL;DR: The current state of the descriptive information-processing model, and its relation to the major topics in empirical aesthetics today, including the nature of aesthetic emotions, the role of context, and the neural and evolutionary foundations of art and aesthetics are reviewed.
Abstract: About a decade ago, psychology of the arts started to gain momentum owing to a number of drives: technological progress improved the conditions under which art could be studied in the laboratory, neuroscience discovered the arts as an area of interest, and new theories offered a more comprehensive look at aesthetic experiences. Ten years ago, Leder, Belke, Oeberst, and Augustin (2004) proposed a descriptive information-processing model of the components that integrate an aesthetic episode. This theory offered explanations for modern art's large number of individualized styles, innovativeness, and for the diverse aesthetic experiences it can stimulate. In addition, it described how information is processed over the time course of an aesthetic episode, within and over perceptual, cognitive and emotional components. Here, we review the current state of the model, and its relation to the major topics in empirical aesthetics today, including the nature of aesthetic emotions, the role of context, and the neural and evolutionary foundations of art and aesthetics.
329 citations