Editing Distributed cognition (section)

==Applications==
The application area of DCog is systems design and implementation in specific work environments. Its main method is [[field research]], going into the workplace and making rigorous observations, e.g. through capturing work performances with video, studying and coding the recorded activities using qualitative research methods to codify the various ways in which cognition is distributed in the local environment, through the social and technical systems with which the workers engage.

Distributed cognition as a theory of learning, i.e. one in which the development of knowledge is attributed to the system of thinking agents interacting dynamically with artifacts, has been widely applied in the field of [[distance education|distance learning]], especially in relation to [[computer-supported collaborative learning]] (CSCL) and other computer-supported learning tools. For example, in the field of teaching English Composition, Kevin LaGrandeur has argued that CSCL provides a source of common memory, collaborative space, and a cognitive artifact (tool to enhance cognition) that allows students to more easily build effective written compositions via explicit and implicit machine-human collaboration. Distributed cognition illustrates the process of interaction between people and technologies in order to determine how to best represent, store and provide access to digital resources and other artifacts.

[[Collaborative tagging]] on the [[World Wide Web]] is one of the most recent developments in technological support for distributed cognition. Beginning in 2004<ref>{{cite book | vauthors = Mika P | chapter = Ontologies are us: A unified model of social networks and semantics. | title = International semantic web conference | series = Lecture Notes in Computer Science | date = November 2005 | volume = 3729 | pages = 522–536 | publisher = Springer | location = Berlin, Heidelberg. | doi = 10.1007/11574620_38 | isbn = 978-3-540-29754-3 }}</ref> and quickly becoming a standard on websites, collaborative tagging allows users to upload or select materials (e.g. pictures, music files, texts, websites) and associate tags with these materials. Tags can be chosen freely, and are similar to keywords. Other users can then browse through tags; a click on a tag connects a user to similarly tagged materials. Tags furthermore enable [[tag cloud]]s, which graphically represent the popularity of tags, demonstrating co-occurrence relations between tags and thus jump from one tag to another.

Dcog has also been used to understand learning and communication in clinical settings and to obtain an integrated view of clinical workplace learning. It has been observed how medical actors use and connect gestural practices, along with visual and haptic structures of their own bodies and of artifacts such as technological instruments and computational devices. In so doing they co-construct complex, multimodal representations that go beyond the mental representations usually studied from a cognitive perspective of learning.<ref name="Pimmer_2013">{{cite journal | vauthors = Pimmer C, Pachler N, Genewein U | title = Reframing clinical workplace learning using the theory of distributed cognition | journal = Academic Medicine: Journal of the Association of American Medical Colleges | volume = 88 | issue = 9 | pages = 1239–45 | date = September 2013 | pmid = 23887014 | doi = 10.1097/ACM.0b013e31829eec0a | s2cid = 12371185 | doi-access = free }}</ref>

Distributed cognition can also be seen through cultures and communities. Learning certain habits or following certain traditions is seen as cognition distributed over a group of people. Exploring distributed cognition through community and culture is one way to understand how it may work.

With the new research that is emerging in this field, the overarching concept of distributed cognition enhances the understanding of interactions between individual human beings and artifacts such as technologies and machines, and complex external environments.{{Nonspecific|date=August 2013}} This concept has been applied to educational research in the areas of [[Distributed Leadership|distributed leadership]] and distributed instruction{{Nonspecific|date=November 2015}}.

Distributed cognition between internal and external processing has also been used to study [[Problem solving|problem-solving]] and [[Bayesian reasoning]]. For example, it has been observed that the use of external manipulable materials such as cards and tokens can help improve performance and reduce [[cognitive bias]] such as the [[Base rate fallacy|base-rate fallacy]], even among adult problem-solvers, as long as they physically interact with these artefacts.<ref>{{cite journal | vauthors = Vallée-Tourangeau G, Abadie M, Vallée-Tourangeau F | title = Interactivity fosters Bayesian reasoning without instruction | journal = Journal of Experimental Psychology. General | volume = 144 | issue = 3 | pages = 581–603 | date = June 2015 | pmid = 26030173 | doi = 10.1037/a0039161 | url = https://eprints.kingston.ac.uk/id/eprint/31315/1/Vallee-Tourangeau-G-31315.pdf }}</ref> It has also been reported that interacting with tokens can reduce the impact of [[mathematical anxiety]] on [[mental calculation]] performance<ref>{{cite journal | vauthors = Vallée-Tourangeau F, Sirota M, Vallée-Tourangeau G | title = Interactivity mitigates the impact of working memory depletion on mental arithmetic performance | journal =   Cognitive Research: Principles and Implications| volume = 1 | issue = 1 | pages = 26 | date = December 2016 | pmid = 28180177 | pmc = 5256453 | doi = 10.1186/s41235-016-0027-2 | doi-access = free }}</ref> and supports [[insight]]<ref>{{cite journal | vauthors = Henok N, Vallée-Tourangeau F, Vallée-Tourangeau G | title = Incubation and interactivity in insight problem solving | journal = Psychological Research | volume = 84 | issue = 1 | pages = 128–139 | date = February 2020 | pmid = 29480412 | pmc = 6994426 | doi = 10.1007/s00426-018-0992-9 }}</ref><ref>{{Cite journal| vauthors = Fleck JI, Weisberg RW |date=2013-06-01|title=Insight versus analysis: Evidence for diverse methods in problem solving |journal=Journal of Cognitive Psychology|volume=25|issue=4|pages=436–463|doi=10.1080/20445911.2013.779248|s2cid=146689726|issn=2044-5911}}</ref> although the evidence is mixed with regards to the impact of distributing cognition between internal and external processing with regards to [[insight]].<ref>{{cite journal | vauthors = Chuderski A, Jastrzębski J, Kucwaj H | title = How physical interaction with insight problems affects solution rates, hint use, and cognitive load | journal = British Journal of Psychology | volume = 112 | issue = 1 | pages = 120–143 | date = February 2021 | pmid = 32125690 | doi = 10.1111/bjop.12442 | s2cid = 211835401 }}</ref>