Abstract
In higher education, the difficulties of implementing teaching sequences in which several academic and engineering disciplines, or even professional worlds, coexist have been widely documented. We hypothesize that these difficulties stem, especially, from a series of conditions and constraints that determine the knowledge life in these different universes. In this chapter, we propose using tools from the Anthropological Theory of Didactics (ATD) to analyze these epistemologies and illustrate their application with examples from land surveying, industrial, and computer science contexts.
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Notes
- 1.
For a presentation of the concept of praxeology, see the 3rd section of the chapter by González-Martín, Barquero and Gueudet.
- 2.
« une deuxième fonction de la technologie est d’expliquer, de rendre intelligible, d’éclairer la technique. […] Enfin une dernière fonction correspond à un emploi plus actuel du terme de technologie: la production de techniques. » (1999, pp. 226–227).
- 3.
For Anglo-Saxon references, see for example Chapter 1, Part 650- Engineering Field Handbook edited by the Natural Resources Conservation Service of the US Department of Agriculture (2008) https://directives.sc.egov.usda.gov/OpenNonWebContent.aspx?content=25276.wba
- 4.
Unknown author and date. http://www.ce.memphis.edu/1112/notes/project_3/traverse/Surveying_traverse.pdf
- 5.
For a presentation of this pedagogy, see the chapter by González-Martín, Barquero and Gueudet.
- 6.
The Western Electric Company closed in 1985. The book is now almost impossible to find, but a French translation is available online.
- 7.
See Chevallard (1991, p. 214).
- 8.
We rely here on Bettayeb (2012), especially p. 36.
- 9.
For a complete presentation of this problematic, see (Joint Committee for Guides in Metrology, 2008).
- 10.
Associating a specific level of confidence requires certain assumptions regarding the probability distribution, characterized by the measurement result and its standard deviation. Normal distribution is often applied as a principle assumption for MS, this explains the shape of the curves in the figures.
- 11.
Measurement device
- 12.
This choice supposes that the enterprise’s metrology laboratory has a good knowledge of the range of variation of a given product.
- 13.
See (Clément, 2017), p. 15.
- 14.
Automotive Industry Action Group (AIAG) sustains these positions. They appear in MSA-2010: Table II-D 1.
- 15.
See (Clément, 2017), p. 10.
- 16.
Patricio-Martinez has worked with a 2012 version of d’Andrea’s paper, which is no longer available. We refer to a 2020 version, similar to the previous one, edited in a review. English translations of the citations are ours.
- 17.
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Castela, C., Romo-Vázquez, A. (2022). Towards an Institutional Epistemology. In: Biehler, R., Liebendörfer, M., Gueudet, G., Rasmussen, C., Winsløw, C. (eds) Practice-Oriented Research in Tertiary Mathematics Education. Advances in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-14175-1_30
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