Distributed Cognition
From ElateWiki
“Distributed cognition” (knowing or mental awareness shared among a group of people who are not co-located) builds on the traditional concept of individual learner-based cognition (the mental process of knowing and thought) by the conceptualization of cognition as a social systems phenomenon. Here, cognition is distributed between the individual and the larger environment as well as between people.
Distributed cognition occurs within social interactions and communications. Cognition is distributed in a learning ecology (a context and environment as well as a cultural space) and is not merely something that occurs inside a learner. Learning is embodied—experienced through the sensory systems and mental filters of individual learners interacting with learning artifacts, environmental elements, and other people. Distributed cognition is communicated into external (to individuals) representations in physical and virtual environments; G. Salomon (1999) suggested that knowledge may be off-loaded to a device like a calculator or computer with cognitive duties placed on the machine.
Theoretically and in application, this means that cognition is distributed among members of a social group with each member holding some unique awareness or experience or knowledge for the group. There may well be shared awarenesses (shared cognitions) among all the members as well. Distributed cognition suggests that there must be a kind of coordination between internal mental and external environmental structures for the distributed awareness. It also suggests that cognitive processes may be distributed in time, with prior cognitions affecting future ones.
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[edit] Theory Origins
This psychological theory was developed by Edwin Hutchins in the mid-1980s. This theory combines insights from cognitive science, Vygotsky (such as his ideas of the zone of proximal development and activity theory), and sociology. The theory suggests that all human cognition is situated in the sociocultural world and cannot exist outside the influence of that world.
This theory may be understood as “cognition in the wild” (to borrow Hutchins’ term) in the sense that it strives to learn from actual practices and decision-making in complex systems. Information processing is not just something that happens in individual minds but in systems and among groups, which rely on the larger environment and on physical artifacts to contain, maintain, distribute, and inspire the ideas.
[edit] Distributed Cognition and E-Learning
Distributed cognition applies to the co-building of learning and knowledge in collaborative digital libraries, online discovery learning spaces, student group work, communities of practice, networks of practice, human-computer interactions, and the design of e-learning spaces. This theory has implications for computer supported collaborative learning (CSCL) and computer supported collaborative work (CSCW) in terms of how collaborative spaces are designed and used.
The basic design concept is to strengthen the processes of distributed cognition: the individual and group meta-cognition, intercommunications, group efficacies, and the recording of distributed cognition in these shared mediated spaces.
[edit] Tools to Enhance Distributed Cognition
Clear naming protocols and orientation measures enhance user uses of virtual collaborative spaces. Those that use 3D immersive spaces need to offer users a clear sense of spatial orientation in the environment as well as awareness of themselves and other people (telepresence and social presences).
The expressiveness of the various tools for expression and design may enable stronger distributed cognition. The reflective tools for individual metacognition (without harmful disruptions or interruptions) may enhance the distributed cognition. The ability for high intercommunications may enhance knowledge proliferation and adoption. More strategic multi-modal communications may strengthen efficient learning of high-load information in crisis situations (Cao, Theune, & Nijholt, 2009). Datamining tools that help virtual community members identify hidden information and patterns may also enhance the cognition. Microblogging tools that allow real-time situational awareness across distances may also be highly beneficial.
Tools that help collaborative communities be aware of their shared cultural aspects and to affect their own cultures constructively will also be important, since cultures are seen to carry some cognitive architectures and understandings—that influence the thinking work. The culture serves as a reservoir of resources for “learning, problem solving, and reasoning” (Hollan, Hutchins, & Kirsh, 2000, p. 178).
Greater ways for virtual communities to conduct “cognitive load-balancing” among its members may also be an important affordance (Hollan, Hutchins, & Kirsh, 2000, p. 181). Ways to capture emergent initiatives and behaviors would also enhance the environmental design. Analytical tools to evaluate the outputs of the community for value and validity may also be helpful. Such tools may be processes for human engagement to collaboratively evaluate the outcomes.
Collaborative tagging is a communal practice that enhances distributed cognition, with various digital resources marked with tags for analysis through tag clouds.
The analysis of socio-technical systems (STS) rests on distributed cognition theory because these show how people interact with each other and technologies in order to achieve complex and shared aims. These situations apply to such areas as navigational systems in ships, flight cockpits of airplanes, air traffic control, and other high-reliability collaborative systems.
Some spaces that enhance distributed cognition involved mixed reality or the use of physical spaces in conjunction with digital augmentations.
[edit] The “Unit of Measure” for Distributed Cognition
The so-called “unit of measure” for distributed cognition then exists at a systems level—to highlight the complex interactions that promote the construction of distributed cognition awarenesses and cooperations. Hollan, Hutchins, and Kirsh observe: “Distributed cognition looks for cognitive processes, wherever they may occur, on the basis of the functional relationships of elements that participate together in the process” (2000, p. 175).
[edit] Perception and Distributed Cognition
Distributed cognition relies on the human sensory organs to collect information for thinking and learning. This suggests the importance of information sharing based on the affordances and constraints of the human perceptual and information processing systems.
[edit] Affect and Distributed Cognition
More current research in distributed cognition brings in issues of affect and emotional intelligence. For example, the “theory of mind” involves the intelligence to read others’ internal states, which is much more complicated to do through computer mediated communications means in distributed or remote teams. In many concepts, human rationality is not primary; rather, emotion is a dual of cognition and affects human learning, judgment, and decision-making. Some suggest that emotion cannot be separated from cognition, and that for many, emotions are more important to fulfill than practical needs regarding some products (Buccini & Padovani, 2007). Emotions are seen as “omnipresent in any kind of interaction” (Ben Ammar & Beji, 2006, p. 1).
[edit] Decision–making and Distributed Cognition
Other works focus on collaborative designs, policy-making, simulations, software design, and other applications of distributed cognition.
[edit] See Also
“Distributed cognition.” (2010, Jan. 12). Wikipedia. Retrieved Feb. 18, 2010, from http://en.wikipedia.org/wiki/Distributed_cognition.
[edit] References
Ben Ammar, M. & Neji, M. (2006). A multi-agent based system for affective peer-e-learning. In the proceedings of the 2nd international conference on Mobile Multimedia Communications: Alghero, Italy. Article 40. 1 – 6.
Buccini, M. & Padovani, S. (2007). Typology of the experiences. In the proceedings of the Designing Pleasurable Products and Interfaces: Helsinki, Finland (pp. 495 – 504).
Cao, Y., Theune, M., & Nijholt, A. (2009). Modality effects on cognitive load and performance in high-load information presentation. IUI 2009: Sanibel Island, Florida (pp. 335 – 344).
Hollan, J., Hutchins, E., & Kirsh, D. (2000). Distributed cognition: Toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction: 7(2), 174 – 196.