Cognition In The Wild
01 Jan 2016-
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TL;DR: Theories of CSCL are shaped by rapidly evolving digital technologies, pedagogical practices, and research methods as mentioned in this paper, and they can be categorized as: subjective (individual cognition and learning), intersubjective (interactional meaning making), and inter-objective (networks of learners, tools, artifacts, and practices).
Abstract: This chapter examines collaborative learning as cognition at the small-group unit of analysis, and highlights theoretical questions concerning interrelationships among individual, collective, and cultural cognition. CSCL is a theory- and research-based pedagogical vision of what collaborative learning could be like, thanks to innovative computational supports and new ways of thinking about learning. Theories of CSCL are shaped by rapidly evolving digital technologies, pedagogical practices, and research methods. Relevant theories can be categorized as: subjective (individual cognition and learning), intersubjective (interactional meaning making), and inter-objective (networks of learners, tools, artifacts, and practices). Theoretical insights suggest ways of enhancing, supporting, and analyzing cognition and learning by individuals, groups, and communities. The emerging ecology of socio-digital participation—involving students’ daily use of computers, mobile devices, social media, and the Internet—requires extending and synthesizing CSCL theories to conceptualize connected learning at multiple levels.
51 citations
Cites background from "Cognition In The Wild"
...But in focusing on what is really the community level—characteristically for a cultural anthropologist—he does not generally analyze the cognitive meaning making of the group itself (but see his analysis of group or organizational learning in Chapter 8 of Hutchins, 1996)....
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...• “The cognitive properties of groups are produced by interaction between structures internal to individuals and structures external to individuals” (Hutchins, 1996, p. 262)....
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...• “The group performing the cognitive task may have cognitive properties that differ from the cognitive properties of any individual” (Hutchins, 1996, p. 176)....
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...Progress in further developing theories of CSCL will require careful analysis of case studies and experimental results guided by theoretical perspectives that are clearly enunciated....
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TL;DR: This article presents a framework for understanding and modeling teams as dynamical systems and describes empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis.
Abstract: By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area.
51 citations
Cites background from "Cognition In The Wild"
...…activity theory (Leont’ev, 1981), coordination dynamics (Kelso, 1995; including interpersonal, Richardson et al., 2005, 2007), distributed cognition (Hutchins, 1996), groups as complex systems (McGrath et al., 2000), interactive team cognition (Cooke et al., 2013), dynamical systems in team sports…...
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..., 2005, 2007), distributed cognition (Hutchins, 1996), groups as complex systems (McGrath et al....
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07 May 2016
TL;DR: Considering how computing as an actor contributes to the construction of publics provides insight into the design of computational systems that address issues, and introduces the idea of the object ecology as a way to coordinate design approaches to computational publics.
Abstract: Social computing-or computing in a social context-has largely concerned itself with understanding social interaction among and between people. This paper asserts that ignoring material components-including computing itself-as social actors is a mistake. Computing has its own agenda and agencies, and including it as a member of the social milieu provides a means of producing design objects that attend to how technology use can extend beyond merely amplifying or augmenting human actions. In this paper, we offer examples of projects that utilize the capacity of object-oriented publics to both analyze the conditions and consequences around existing publics and engage with matters of concern inherent to emerging publics. Considering how computing as an actor contributes to the construction of publics provides insight into the design of computational systems that address issues. We end by introducing the idea of the object ecology as a way to coordinate design approaches to computational publics.
50 citations
Cites background from "Cognition In The Wild"
...Even returning to distributed cognition [36,37], we can see the trajectory that externalized cognitive tools are not just repositories of some prefigured human cognition, but are discrete actors with agency engaged discursively with their social context....
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...Much in the way distributed cognition allowed cognition to escape the confines of the skull [36], material agency opens the field of analysis for understanding social effects as the result of hybrid human/nonhuman collectives....
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09 Aug 2015
TL;DR: This analysis shows how a system of students, teachers, and tools, working in a music classroom, is able to accomplish conceptually demanding computer music programming.
Abstract: Research on students' learning in computing typically investigates how to enable individuals to develop concepts and skills, yet many forms of computing education, from peer instruction to robotics competitions, involve group work in which understanding may not be entirely locatable within individuals' minds. We need theories and methods that allow us to understand learning in cognitive systems: culturally and historically situated groups of students, teachers, and tools. Accordingly, we draw on Hutchins' Distributed Cognition [16] theory to present a qualitative case study analysis of interaction and learning within a small group of middle school students programming computer music. Our analysis shows how a system of students, teachers, and tools, working in a music classroom, is able to accomplish conceptually demanding computer music programming. We show how the system does this by 1) collectively drawing on individuals' knowledge, 2) using the physical and virtual affordances of different tools to organize work, externalize knowledge, and create new demands for problem solving, and 3) reconfiguring relationships between individuals and tools over time as the focus of problem solving changes. We discuss the implications of this perspective for research on teaching, learning and assessment in computing.
50 citations
TL;DR: This paper developed a conceptualization of embodied metaphor as a form of cultural cognition in action and demonstrated that fasting reshaped converts' subjectivities and subsequent actions through the creation of a series of metaphorical associations between concrete, bodily experiences related to food, hunger, and appetite and more abstract religious discourses pertaining to the soul, sin, and the acquisition of religious virtue.
Abstract: Drawing from an ethnographic study of fasting among converts to Eastern Orthodox Christianity in the United States, this article develops a conceptualization of embodied metaphor as a form of cultural cognition in action. The findings demonstrate that fasting reshaped converts’ subjectivities and subsequent actions through the creation of a series of metaphorical associations between concrete, bodily experiences related to food, hunger, and appetite and more abstract religious discourses pertaining to the soul, sin, and the acquisition of religious virtue. While current influential models of cultural cognition in sociology have focused on explaining the divide between cognition at the semantic level of discourse (i.e., discursive consciousness) and the somatic level of bodily perception and habit (i.e., practical consciousness), this study argues that embodied metaphor is a cognitive process that accounts for the dynamic, mutually informing interactions between these two cognitive registers. By way of conclusion, I argue for the broader theoretical, methodological, and empirical significance of this study for sociological scholarship on culture and cognition.
50 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