Article Gold Open Access 2014

A boundary-crossing approach to support students' integration of statistical and work-related knowledge

Educational Studies in Mathematics
Journal · Vol. 86 · Issue 2 · pp. 223-237
Abstract

Vocational students and beginning professionals typically find it hard to integrate the mathematics and statistics that they have learned at school with work-related knowledge. To explore how such an integration process could be supported, we conducted an intervention in secondary vocational laboratory education. Our boundary-crossing approach was informed by the literature on boundary crossing and accompanying learning mechanisms (e.g., reflection in the form of perspective making and taking, and transformation in the form of hybridization). We hypothesized that reflection, as making and taking perspectives on school-taught and work-related knowledge, could lead to transformation, i.e., help students integrate these types of knowledge into a hybridized whole. Data collection included video and audio recordings of five 1-h meetings with three students, the data from their research projects, and interviews with the teacher and two workplace supervisors. The analysis of the students' reasoning during the meetings revealed that their level of integrating school-taught statistics and work-related knowledge increased significantly and with a medium effect size. This suggests that a boundary-crossing approach can support students in integrating school-taught and work-related knowledge. © 2013 The Author(s).

Keywords

Author Keywords

Internship Boundary object Reflection Knowledge integration Workplace mathematics Vocational mathematics

Index Keywords

Author Affiliations
Freudenthal Institute, Utrecht, Netherlands
Universiteit Utrecht, Utrecht, Netherlands
Funding & Acknowledgements
Grant: 411-06-205
Acknowledgments We acknowledge funding by the Netherlands Organization for Scientific Research (NWO-PROO), under grant number 411-06-205. Thanks also to Xaviera van Mierlo for assisting in the data collection and to Bert Nijdam and Michiel Veldhuis for their statistical advice. We thank Gail FitzSimons for her insightful comments and corrections to earlier versions of this manuscript.
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