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.
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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
Cites methods from "Cognition In The Wild"
...Researchers concerned with the distributed nature of cognitive processes have made this observation as well, using a very different conceptual framework to describe it (Hutchins, 1995; Perry, 2010)....
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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
Cites background or methods from "Cognition In The Wild"
...Other terms for the perspective I refer to as situative include sociocultural psychology (Cole, 1996; Rogoff, 1995), activity theory (Engeström, 1993 ; 1999), distributed cognition (Hutchins, 1995a), and ecological psychology (Gibson, 1979; Reed, 1996)....
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...Material and other informational resources also contribute to the construction of information, in ways investigated in research on distributed cognition (e.g., Hutchins, 1995a) and in social studies of science (e.g., Pickering, 1995)....
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...The problemsolving processes of the lab were distributed throughout the cognitive system, which comprised both the researchers and the cognitive artifacts that they use (cf. Hutchins, 1995a)....
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...For example, Hutchins (1995b) studied remembering in the activity of flying commercial airplanes and gave an analysis of remembering to change the settings of flaps and slats during a descent as an accomplishment of the activity system of the cockpit, including the two pilots along with instruments…...
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...Other terms for the perspective I refer to as situative include sociocultural psychology (Cole, 1996; Rogoff, 1995), activity theory (Engeström, 1993 ; 1999), distributed cognition (Hutchins, 1995a), and ecological psychology (Gibson, 1979; Reed, 1996)....
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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
Cites background from "Cognition In The Wild"
...Social translations are also involved in the interactions between people and artefacts during innovation (Hutchins, 1995)....
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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
Cites background from "Cognition In The Wild"
...By highlighting the role of contextual factors on aesthetic experience, themodelwas alignedwith the growing realization that cognition is contextually situated (Clark, 1997; Hutchins, 1995), and with evidence showing that presentation format influences interest and liking ratings of artworks, even though it has little effect on formal features, such as complexity or composition (Locher et al....
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...…of contextual factors on aesthetic experience, themodelwas alignedwith the growing realization that cognition is contextually situated (Clark, 1997; Hutchins, 1995), and with evidence showing that presentation format influences interest and liking ratings of artworks, even though it has little…...
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References
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Dissertation•
28 Nov 2016
TL;DR: Lupton et al. as mentioned in this paper present an eclairage comprehensif sur les pratiques numeriques de quantification de soi, in particular lorsqu'il s'agit de la sante des individus.
Abstract: Cette these porte sur les pratiques et les usages numeriques de quantification de soi. Le mouvement Quantified Self est apparu initialement en 2007 dans la Silicon Valley, mais en quelques annees ces pratiques ont rapidement evolue pour converger vers les technologies numeriques en sante. S’il ressort de la litterature scientifique et academique qu’elles constituent une forme contemporaine de biopouvoir (Lupton, 2016) et qu’elles sont porteuses de nombreux espoirs dans le domaine de la sante, elles ne sont pourtant pas questionnees, ni du point de vue des mutations anthropologiques qu’elles introduisent dans le couplage entre organisme physiologique et donnees numeriques (Simondon, 1958 ; Boullier, 2011 ; Sadin, 2013), ni du point de vue des modeles de conception sous-jacents aux technologies de quantification de soi, essentiellement fondees sur des approches comportementales, privilegiant la persuasion plutot que la signification. Ce manque de reflexion souleve de nombreuses questions d’ordre ethique quant a la maniere de concevoir des dispositifs numeriques, en particulier lorsqu’il s’agit de la sante des individus (Lupton, 2013 ; 2016). Dans cette perspective, cette these poursuit un double objectif. Le premier est d’apporter un eclairage comprehensif sur les pratiques numeriques de quantification de soi. Le second se rapporte a l’instrumentation de ces nouveaux objets technologiques et a leur modelisation en amont de leur conception. Pour ce faire, nous avons choisi le modele Learning by expanding d’Engestrom (1999, 2014) qui permet d’envisager la conception sous l’angle de la mediation.
23 citations
TL;DR: An alternative perspective on organizational cognition based on e-cognition is offered whereby appeal to systemic cognition replaces the traditional computational model of the mind that is still extremely popular in organizational research.
Abstract: This article offers an alternative perspective on organizational cognition based on e-cognition whereby appeal to systemic cognition replaces the traditional computational model of the mind that is still extremely popular in organizational research It uses information processing, not to explore inner processes, but as the basis for pursuing organizational matters To develop a theory of organizational cognition, the current work presents an agent-based simulation model based on the case of how individual perception of scientific value is affected by and affects organizational intelligence units' (eg, research groups', departmental) framing of the notorious impact factor Results show that organizational cognition cannot be described without an intermediate meso scale – called here social organizing – that both filters and enables the many kinds of socially enabled perception, action and behavior that are so characteristic of human cognition
23 citations
TL;DR: In this paper, a systematic survey of the various attitudes proponents of enaction (or enactivism) entertained or are entertaining towards representationalism and towards the use of the concept of mental representation in cognitive science is presented.
Abstract: I propose a systematic survey of the various attitudes proponents of enaction (or enactivism) entertained or are entertaining towards representationalism and towards the use of the concept “mental representation” in cognitive science. For the sake of clarity, a set of distinctions between different varieties of representationalism and anti-representationalism are presented. I also recapitulate and discuss some anti-representationalist trends and strategies one can find the enactive literature, before focusing on some possible limitations of eliminativist versions of enactive anti-representationalism. These limitations are here taken as opportunities for reflecting on the fate of enactivism in its relations with representationalism and anti-representationalism.
23 citations
TL;DR: In this paper, the authors investigate the observational practices of amateur astronomers and take an interactionist perspective and examine how the body is recruited and recruited to perform an activity in the field of astronomy.
Abstract: We add to research on embodied cognition by investigating the observational practices of amateur astronomers. Specifically, we take an interactionist perspective and examine how the body is recruit...
23 citations
TL;DR: An end-to-end convolutional neural network model which simultaneously implements aesthetic classification and understanding is proposed and it is found that dropping out ambiguous image is a special case of the sample-specific method, and also figure out that as the weights of the non-ambiguous images increase, the performance is positively affected.
Abstract: Currently image aesthetic estimation using deep learning has achieved great success compared with the traditional methods by hand-crafted features. Similar to recognition problem, aesthetic estimation categorizes images into visually appealing or not. Nevertheless, it is desirable to understand why certain images are visually more appealing, in specific, which part of the image is contributing to the aesthetic preference. In fact, most traditional approaches adopting hand-crafted feature are, to some extent, able to understand part of image’s aesthetic and content information while few studies have been conducted in the context of deep learning. Moreover, we discover that aesthetic rating is ambiguous so that many examples are uncertain in aesthetic level. This has caused a highly imbalanced distribution of aesthetic ratings. To tackle all these issues, we propose an end-to-end convolutional neural network (CNN) model which simultaneously implements aesthetic classification and understanding. To overcome the imbalanced aesthetic ratings, a sample-specific classification method that re-weights samples’ importance is proposed. We find that dropping out ambiguous image, as common adopted by recent deep learning models, is a special case of the sample-specific method, and also figure out that as the weights of the non-ambiguous images increase, the performance is positively affected. In order to understand what is learned in the deep model, global average pooling (GAP) following the last feature map is employed to generate aesthetic activation map (AesAM) and attribute activation map (AttAM). AesAM and AttAM respectively represent the likelihood of aesthetic level for spatial location, and the likelihood of different attribute information. In particular, AesAM mainly accounts for what is learned in deep model. Experiments are carried out on public aesthetic datasets and state-of-the-art performance is achieved. Thanks to the introduction of AttAM, the aesthetic preference is explainable by visualization. Finally, a simple application on image cropping based on the AesAM is presented. The code and trained model will be publicly available on https://github.com/galoiszhang/AWCU .
23 citations