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Varma Sashank & Schwartz Daniel L. (2008). « How should educational neuroscience conceptualise the relation between cognition and brain function? Mathematical reasoning as a network process ». Educational Research, vol. 50, n° 2, p. 149–161. ISSN 0013-1881. En ligne : <http://www.tandfonline. ... .1080/00131880802082633>. 
Added by: Catherine Reverdy (25 Jul 2013 11:52:08 Europe/Paris)
Resource type: Journal Article
DOI: 10.1080/00131880802082633
ID no. (ISBN etc.): 0013-1881
BibTeX citation key: Varma2008
Categories: Apprentissages et psychologie
Subcategories: Neurosciences et Ă©ducation
Keywords: neurosciences
Creators: Schwartz, Varma
Collection: Educational Research
Views: 978/1135
Views index: 14%
Popularity index: 3.5%
URLs     http://www.tandfon ... /00131880802082633
Abstract     
Background: There is increasing interest in applying neuroscience findings to topics in education. Purpose: This application requires a proper conceptualisation of the relation between cognition and brain function. This paper considers two such conceptualisations. The area focus understands each cognitive competency as the product of one (and only one) brain area. The network focus explains each cognitive competency as the product of collaborative processing among multiple brain areas. Sources of evidence: We first review neuroscience studies of mathematical reasoning–specifically arithmetic problem-solving and magnitude comparison–that exemplify the area focus and network focus. We then review neuroscience findings that illustrate the potential of the network focus for informing three topics in mathematics education: the development of mathematical reasoning, the effects of practice and instruction, and the derailment of mathematical reasoning in dyscalculia. Main argument: Although the area focus has historically dominated discussions in educational neuroscience, we argue that the network focus offers a complementary perspective on brain function that should not be ignored. Conclusions: We conclude by describing the current limitations of network-focus theorising and emerging neuroscience methods that promise to make such theorising more tractable in the future.
Added by: Catherine Reverdy  
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