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Tool use as distributed cognition: how tools help, hinder and define manual skill

Overview of attention for article published in Frontiers in Psychology, January 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

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2 Facebook pages

Citations

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28 Dimensions

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78 Mendeley
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Title
Tool use as distributed cognition: how tools help, hinder and define manual skill
Published in
Frontiers in Psychology, January 2014
DOI 10.3389/fpsyg.2014.00116
Pubmed ID
Authors

Chris Baber, Manish Parekh, Tulin G. Cengiz

Abstract

Our thesis in this paper is that, in order to appreciate the interplay between cognitive (goal-directed) and physical performance in tool use, it is necessary to determine the role that representations play in the use of tools. We argue that rather being solely a matter of internal (mental) representation, tool use makes use of the external representations that define the human-environment-tool-object system. This requires the notion of Distributed Cognition to encompass not simply the manner in which artifacts represent concepts but also how they represent praxis. Our argument is that this can be extended to include how artifacts-in-context afford use and how this response to affordances constitutes a particular form of skilled performance. By artifacts-in-context, we do not mean solely the affordances offered by the physical dimensions of a tool but also the interaction between the tool and the object that it is being used on. From this, "affordance" does not simply relate to the physical appearance of the tool but anticipates subsequent actions by the user directed towards the goal of changing the state of the object and this is best understood in terms of the "complimentarity" in the system. This assertion raises two challenges which are explored in this paper. The first is to distinguish "affordance" from the adaptation that one might expect to see in descriptions of motor control; when we speak of "affordance" as a form of anticipation, don't we just mean the ability to adjust movements in response to physical demands? The second is to distinguish "affordance" from a schema of the tool; when we talk about anticipation, don't we just mean the ability to call on a schema representing a "recipe" for using that tool for that task? This question of representation, specifically what knowledge needs to be represented in tool use, is central to this paper.

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X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
United States 1 1%
Unknown 75 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 32%
Researcher 15 19%
Student > Postgraduate 6 8%
Student > Master 5 6%
Student > Doctoral Student 5 6%
Other 18 23%
Unknown 4 5%
Readers by discipline Count As %
Psychology 25 32%
Social Sciences 9 12%
Computer Science 8 10%
Business, Management and Accounting 5 6%
Neuroscience 4 5%
Other 21 27%
Unknown 6 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 July 2014.
All research outputs
#3,102,404
of 24,143,470 outputs
Outputs from Frontiers in Psychology
#5,902
of 32,434 outputs
Outputs of similar age
#36,316
of 314,515 outputs
Outputs of similar age from Frontiers in Psychology
#60
of 180 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 32,434 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 314,515 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 180 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.