Mathematical modelling – a key to citizenship education
Katja Maass (),
Michèle Artigue (),
Hugh Burkhardt (),
Michiel Doorman (),
Lyn D. English (),
Vincent Geiger (),
Konrad Krainer (),
Despina Potari () and
Alan Schoenfeld ()
Additional contact information
Katja Maass: Pädagogische Hochschule Freiburg, International Centre for STEM Education
Michèle Artigue: Université de Paris/LDAR, Laboratoire de Didactique André Revuz
Hugh Burkhardt: University of Nottingham
Michiel Doorman: Utrecht University/Freudenthal Institute
Lyn D. English: Queensland University of Technology
Vincent Geiger: Australian Catholic University, Institute of Learning Science and Teacher Education
Konrad Krainer: Universität Klagenfurt
Despina Potari: National and Kapodistrian University of Athens, Department of Mathematics
Alan Schoenfeld: University of California, Graduate School of Education
Chapter Kapitel 2 in Initiationen mathematikdidaktischer Forschung, 2022, pp 31-50 from Springer
Abstract:
Abstract The pandemic has demonstrated more than ever that citizens around the world need to understand how mathematics contributes to understanding global challenges and ways of overcoming them. People need to understand that predictions are based on models that make use of assumptions and the best inputs available. They also need to learn to critically evaluate reports based on the outcomes of models to make effective decisions and deal with the inherent uncertainty in an appropriate way. These capabilities make it clear that mathematical modelling is a key element of citizenship education. Given this fundamental role of modelling, we take a closer look at its definition, its history, its connection to other teaching approaches, as well as the competences students need to carry through modelling processes and the competences teachers need for teaching modelling.
Keywords: Mathematical modelling; Citizenship education; Modelling competences; Teaching modelling; Large scale implementation in day-to-day teaching (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-658-36766-4_2
Ordering information: This item can be ordered from
http://www.springer.com/9783658367664
DOI: 10.1007/978-3-658-36766-4_2
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().