Quantitative Reasoning and Mathematical Modeling in the Sciences: A Virtual Conversation

Document Type

Contribution to Book

Publication Date

2011

Publication Title

WISDOMe Monograph: New Perspectives and Directions for Collaborative Research in Mathematics Education.

Abstract

Mathematics education, STMC, Science and Mathematics Teaching Center, University of Wyoming

In Sprint 2011 the University of Wyoming Science and Mathematics Teaching Center (STMC) hosted the Quantitative Reasoning and Mathematical Modeling in Science Seminar. This virtual seminar invited speakers from across the country to discuss aspects of quantitative reasoning and mathematical modeling in the sciences. This article summaries the collective wisdom shared by these speakers, serving as an overview of a full monograph on quantitative reasoning and mathematical modeling to be developed in 2011-2012.

Quantitative reasoning and mathematical modeling was identified as one of three critical themes in mathematics education by the Wyoming Institute for the Study and Development of Mathematical Education (WISDOMe). The WISDOMe) collaborative research community, directed by Larry Hatfiedld, convened experts and early career researchers to explore the three themes:

Theme 1: DIME – Developing Investigations of Mathematical Experience

Theme 2: TTAME – Technology Tools and Applications in Mathematics Education

Theme 3: QRaMM – Quantitative Reasoning and Mathematics Modeling

In Spring 2011 the University of Wyoming Science and Mathematics Teaching Center (SMTC) followed up on the WISDOMe Conference held in Fall2 010 by hosting a virtual seminar on the QRaMM theme. The QRaMM in Science seminar was coordinated by Robert Mayes, who brought speakers together with a cohert of graduate student to discuss multiple asects of QR and modeling from the perspective of different fields. A docket of the speakers in the seminar is provided in table 1. The speakers brought perspectives on quantitative reasoning QR and modeling in the sciences from scientists, mathematicians, science educators and mathematics educators. In this paper we will present a summary of these perspective by field, providing key conceptual components of QR andmodeling as well as exemplars.

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