# Measurement in occupations

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==References== | ==References== | ||

+ | * Bakker, A., Kent, P., Noss, R. and Hoyles, C. (2009). {{refworks|Alternative representations of statistical measures in computer tools to promote communication between employees in automotive manufacturing|3598}}. Technology Innovations in Statistics Education, 3(2). | ||

+ | * Bakker, A., Kent, P., Derry, J., Noss, R. and Hoyles, C. (2008). {{refworks|Statistical inference at work: The case of statistical process control|3599}}. Statistics Education Research Journal, 7(2), 130-145. | ||

+ | * Hoyles, C., Bakker, A., Kent, P. and Noss, R. (2007). {{refworks|Attributing meanings to representations of data: The case of statistical process control |3597}}. Mathematical Thinking and Learning, 9, 331-360. | ||

+ | * Hoyles, C., Noss, R., Kent, P. and Bakker, A. (2010). {{refworks|Improving mathematics at work: The need for techno-mathematical literacies|3601}}. London: Routledge. | ||

+ | * Konold, C. and Lehrer, R. (2008). {{refworks|Technology and mathematics education: An essay in honor of Jim Kaput|3591}} (In L. D. English (Ed.), Handbook of international research in mathematics education (2nd ed.). New York: Routledge. | ||

* [[Measurement (General)]] | * [[Measurement (General)]] | ||

## Revision as of 06:16, 2 August 2010

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* Meten_in_het_beroep (dutch)

## General

This paper analyzes the nature and purposes of measurement in intermediate-level work, i.e. occupations for which Dutch senior secondary vocational education (MBO) prepares its students (aged 16+). A quantitative analysis was based on the 237 qualification files describing the competencies required in each of the MBO occupations, and a qualitative analysis was carried out on interview data in different educational programs with a focus on optician and lab technician. Half of the qualification files explicitly mention measurement in their competence indicators. More reference to measurement is made in the technical and business sectors than in the health care and agricultural sectors. In terms of the nature of measurement, we observed that occupational measurement has connections to arithmetic, geometry, data analysis, or science. Most notable, however, is the trend for mediation of measurement by digital technologies, which raises the question of how to prepare vocational students.

Many MBO teachers prefer to start with old technologies in order to give students the opportunities to learn about what happens in the black boxes behind digital displays. The purposes of measurement in intermediate-level occupations can be categorized as meeting quality standards, stock and time management, monitoring production processes as well as their efficiency and effectiveness, making something fit (furniture, automotive assembly), and ensuring safety. Last, some implications for mathematics education are discussed.

## References

- Bakker, A., Kent, P., Noss, R. and Hoyles, C. (2009). Alternative representations of statistical measures in computer tools to promote communication between employees in automotive manufacturing. Technology Innovations in Statistics Education, 3(2).
- Bakker, A., Kent, P., Derry, J., Noss, R. and Hoyles, C. (2008). Statistical inference at work: The case of statistical process control. Statistics Education Research Journal, 7(2), 130-145.
- Hoyles, C., Bakker, A., Kent, P. and Noss, R. (2007). Attributing meanings to representations of data: The case of statistical process control . Mathematical Thinking and Learning, 9, 331-360.
- Hoyles, C., Noss, R., Kent, P. and Bakker, A. (2010). Improving mathematics at work: The need for techno-mathematical literacies. London: Routledge.
- Konold, C. and Lehrer, R. (2008). Technology and mathematics education: An essay in honor of Jim Kaput (In L. D. English (Ed.), Handbook of international research in mathematics education (2nd ed.). New York: Routledge.
- Measurement (General)

## Versions of this document

- 20100801, wikiteam