Probability Modeling and Thinking: What Can We Learn from Practice?

Autor/inn/en	Pfannkuch, Maxine; Budgett, Stephanie; Fewster, Rachel; Fitch, Marie; Pattenwise, Simeon; Wild, Chris; Ziedins, Ilze
Titel	Probability Modeling and Thinking: What Can We Learn from Practice?
Quelle	In: Statistics Education Research Journal, 15 (2016) 2, S.11-37 (27 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1570-1824
Schlagwörter	Statistics; Probability; Teaching Methods; Foreign Countries; Mathematical Models; Simulation; Thinking Skills; Interviews; Research Methodology; Qualitative Research; Mathematics; Mathematics Education; Mathematical Applications; Technology Uses in Education; New Zealand + Suchen Sie Ihr Suchwort? Statistik; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Teaching method; Lehrmethode; Unterrichtsmethode; Ausland; Mathematical model; Mathematisches Modell; Simulation program; Simulationsprogramm; Denkfähigkeit; Interviewing; Interviewtechnik; Research method; Forschungsmethode; Qualitative Forschung; Mathematik; Mathematische Bildung; Angewandte Mathematik; Innermathematische Anwendung; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Neuseeland
Abstract	Because new learning technologies are enabling students to build and explore probability models, we believe that there is a need to determine the big enduring ideas that underpin probabilistic thinking and modeling. By uncovering the elements of the thinking modes of expert users of probability models we aim to provide a base for the setting of new and more relevant goals for probability education in the 21st century. We interviewed seven practitioners, whose professional lives are centered on probability modeling over a diverse range of fields including the development of probability theory. A thematic analysis approach produced four frameworks: (1) probability modeling approaches; (2) probabilistic thinking approaches to a problem; (3) a probability modeling cycle; and (4) core building blocks for probabilistic thinking and modeling. The main finding was that seeing structure and applying structure were important aspects of probability modeling. The implications of our findings for probability education are discussed. (As Provided).
Anmerkungen	International Association for Statistics Education and the International Statistical Institute. PO Box 24070, 2490 AB The Hague, The Netherlands. Tel: +31-70-3375737; Fax: +31-70-3860025; e-mail: isi@cbs.nl; Web site: http://www.stat.auckland.ac.nz/~iase/serj
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01