Quantitative Reasoning in Mathematics and Science Education

by Gïlseren Karagïz Akar (Editor), Ismail ïzgïr Zembat (Editor), Selahattin Arslan (Editor), Patrick W. Thompson (Editor)

Overview

This book focuses on quantitative reasoning as an orienting framework to analyse learning, teaching and curriculum in mathematics and science education. Quantitative reasoning plays a vital role in learning concepts foundational to arithmetic, algebra, calculus, geometry, trigonometry and other ideas in STEM. The book draws upon the importance of quantitative reasoning and its crucial role in education. It particularly delves into quantitative reasoning related to the learning and teaching diverse mathematics and science concepts, conceptual analysis of mathematical and scientific ideas and analysis of school mathematics (K-16) curricula in different contexts. We believe that it can be considered as a reference book to be used by researchers, teacher educators, curriculum developers and pre- and in-service teachers. 

Product Details

ISBN-13:	9783031145537
Publisher:	Springer-Verlag New York, LLC
Publication date:	01/01/2023
Series:	Mathematics Education in the Digital Era , #21
Sold by:	Barnes & Noble
Format:	eBook
File size:	30 MB
Note:	This product may take a few minutes to download.

About the Author

Graduating (1993-1996) from the Department of Mathematics Education in Middle East Technical University, Turkey, Gülseren Karagöz Akar earned her master’s degree in 2001 and PhD in December 2006 in Mathematics Education at the Pennsylvania State University where she continued her post-doctoral studies and worked as a full-time instructor between January 2007 and July 2008. In 2010, she started working at Boğaziçi University, Turkey, as a full time professor where she worked as the head of the Department of Mathematics and Science Education from 2018 to 2021. She was involved in the development of Turkish National Mathematics Program for Gifted (K-12) in 2018 and served as an International Advisory Board member for Journal for Research in Mathematics Education (JRME) between July 2018 and July 2021. Her research involves development of mathematical concepts and the nature of mathematics teacher knowledge. 

Table of Contents

Introductory chapter

Patrick Thompson, Arizona State University, AZ, USA

1 Forming abstracted quantitative structures

Kevin Moore, University of Georgia, GA, USA

2 Different forms of covariation

Heather Johnson, University of Colorado, CO, USA

3 Multiplication and Division in curriculum through QR

Tad Watanabe – Kennesaw State University, GA, USA 

Gülseren Karagöz Akar – Boğaziçi University, İstanbul, Turkey

Nurdan Turan - Boğaziçi University, İstanbul, Turkey

4 Relation between multiplicative/additive reasoning and QR in the context of whole and rational numbers

Terezinha Nunes, University of Oxford, Oxford, UK

Peter Bryant, University of Oxford, Oxford, UK

5 Linear& Non-linear relations through covariation

Teo Paoletti, Montclair State University, NJ, USA

6 Linear, quadratic, exponential functions through QR

Amy Ellis, University of Georgia, GA, USA

Zekiye Özgür, Dokuz Eylül University, İzmir, Turkey

Mehmet Fatih Doğan, Adıyaman University, Adıyaman, Turkey

7 Interpreting graphs of quadratic functions via QR

Aytug Özaltun Çelik, Pamukkale University, Denizli, Turkey

Esra Bukova Güzel, Dokuz Eylül University, İzmir, Turkey

8 Logarithms and/or exponential growth  

Marilyn Carlson – Arizona State University, AZ, USA

9 Geometric transformations through QR

Gülseren Karagöz Akar, Boğaziçi University, İstanbul, Turkey

İsmail Özgür Zembat, University of Glasgow, Glasgow, UK

Selahattin Arslan, Trabzon University, Trabzon, Turkey

Mervenur Belin, Boğaziçi University, İstanbul, Turkey

10 Mathematization of science through QR

Hui Jin – Educational Testing Service, Princeton, USA

Dante Cisterna, Educational Testing Service, Princeton, USA

Hyo Jeong Shin, Educational Testing Service, Princeton, USA

11 Physics Quantitative Literacy through QR

Suzanne White Brahmia, University of Washington, VA, USA

Alexis Olsho, University of Washington, VA, USA

12 Modelling climate change with QR

Dario Gonzales, Universidad de Chile, Chile

 

13 Quantitative Reasoning in Undergraduate Biology

Robert Mayes