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
More filters
TL;DR: It is found that verbal synchrony in large groups produced affiliation, enhanced memory performance, and increased group members’ coordinative efforts, suggesting that the effects of synchrony are stable across modalities, can be generalized to larger groups and have consequences for action coordination.
Abstract: While synchronized movement has been shown to increase liking and feelings of togetherness between people, we investigated whether collective speaking in time would change the way that larger groups played a video game together. Anthropologists have speculated that the function of interpersonal coordination in dance, chants, and singing is not just to produce warm, affiliative feelings, but also to improve group action. The group that chants and dances together hunts well together. Direct evidence for this is sparse, as research so far has mainly studied pairs, the effects of coordinated physical movement, and measured cooperation and affiliative decisions. In our experiment, large groups of people were given response handsets to play a computer game together, in which only joint coordinative efforts lead to success. Before playing, the synchrony of their verbal behavior was manipulated. After the game, we measured group members' affiliation toward their group, their performance on a memory task, and the way in which they played the group action task. We found that verbal synchrony in large groups produced affiliation, enhanced memory performance, and increased group members' coordinative efforts. Our evidence suggests that the effects of synchrony are stable across modalities, can be generalized to larger groups and have consequences for action coordination.
34 citations
Cites background from "Cognition In The Wild"
...For example, Hutchins (1995) observed the ways that navy navigators would distribute cognitive processes between themselves by using external tools and representations, such as maps and notations....
[...]
TL;DR: In this paper, the authors define a belief as a mental representation that influences the practice of a teacher if and only if the belief is active in cognition, and provide implications arising from this definition of belief for both science teacher educators and those who conduct research on the beliefs of both preservice and in-service science teachers.
Abstract: Much research has shown that a science teacher’s beliefs are related to their teaching practice. This line of research has often defined “belief” epistemologically. That is, beliefs are often defined relative to other mental constructs, such as knowledge, dispositions, or attitudes. Left unspecified is the role beliefs play in cognition and how they come to influence science teachers’ classroom practice. As such, researchers and science teacher educators have relied on an (at times, implicit) assumption that there is a direct causal relationship between teachers’ beliefs and classroom practice. In this paper, we propose an operational, as opposed to epistemological, definition of belief. That is, we are explicit about the role a belief plays in science teachers’ cognition and how that leads to classroom practice. We define a belief as a mental representation that influences the practice of a teacher if and only if the belief is active in cognition. We then turn our attention to two limitations in the literature on that have arisen via previous definitions and assumptions regarding science teacher beliefs, showing how defining beliefs operationally helps think about these issues in new ways. The two limitations surround: (1) the difficulty in precisely delineating belief from knowledge; and (2) the interconnectedness of beliefs such that they draw meaning from one another. We then show how our definition of beliefs is congruent with other models of teacher cognition reported in the literature. Finally, we provide implications arising from this definition of belief for both science teacher educators and those who conduct research on the beliefs of both preservice and in-service science teachers.
34 citations
Cites background from "Cognition In The Wild"
...For example, Hutchins (1995) puts forth a model of situated cognition that requires internal mental representations while also recognizing the role that contexts play in influencing both the content of representations in long-term and short-term memory and the activation pattern of those…...
[...]
...Hutchins (1995) argues that cognition is organized fundamentally around the tools we use to create tasks, but he still assumes cognition itself is happening in the head....
[...]
TL;DR: A view of creativity as disconnected from the real world has led to a view of imagination as an imaginative and deliberate mental activity as mentioned in this paper, which can lead to a negative attitude towards creativity.
Abstract: Scholars in sociology and social psychology typically represent creativity as an imaginative and deliberate mental activity. Such a perspective has led to a view of creativity as disconnected from ...
34 citations
TL;DR: It is explained how the integrative perspective may offer starting points for a refined understanding of the sub-processes involved in organizational learning and unlearning and may support a better understanding of practical problems related to organizationallearning and change.
Abstract: Contemporary research into socio-cognitive foundations of organizational learning tends to disregard the distinction between declarative and non-declarative knowledge. By reviewing the literature from organizational learning research and cognitive psychology we explain that this distinction is crucial. We describe the foundations of organizational learning by referring to models that consider the interplay between individual and collective knowledge-related processes in organizations. We highlight the existence of a research gap resulting from the finding that these approaches have widely neglected the existence of different types of knowledge. We then elaborate on characteristics of declarative and non-declarative knowledge in general, consider organizations as structures of distributed cognition, and discuss the relationship between organizational knowledge and practice. Subsequently, we examine the role of declarative and non-declarative knowledge in the context of organizational learning. Here, we analyze (1) the cognitive and social mechanisms underlying the development of declarative and non-declarative knowledge within structures of distributed cognition; and (2) the relationship between alterations in declarative and non-declarative types of knowledge on the one hand and changes in organizational practice on the other. Concluding, we discuss implications of our analysis for organizational learning research. We explain how our integrative perspective may offer starting points for a refined understanding of the sub-processes involved in organizational learning and unlearning and may support a better understanding of practical problems related to organizational learning and change.
33 citations
Cites background from "Cognition In The Wild"
...First, incoming information must be processed and “encoded”; second, information must be retained and “stored” in some way; third, information must be accessed and “retrieved”....
[...]
...…individual knowledge is continuously being exploited and further developed through the communication, integration, and combination of individually held declarative and non-declarative knowledge (Tsoukas, 1996; Thompson et al., 1999; see also Hutchins, 1995a,b; Salomon, 1997; Baber et al., 2014)....
[...]
TL;DR: For example, Heraclitus as mentioned in this paper states that "If you do not expect the unexpected, you will not find it; for it is hard to be sought out and difficult".
Abstract: ἐὰν μὴ ἔλπηται ἀνέλπιστον οὐκ ἐξϵυρήσϵι, ἀνϵξϵρϵύνητον ἐὸν καὶ ἄπορον. (‘If you do not expect the unexpected, you will not find it; for it is hard to be sought out and difficult’) Heraclitus (DK 1...
33 citations
References
More filters
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
[...]
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