From Gatekeeper to Gateway---The Role of Quantitative Reasoning
Abstract
We present Quantitative Reasoning (QR) as a pathway to smooth students’ mathematical transition from high school to higher education. We explain what QR is, why it is important, and for whom it is most appropriate. A current leader in the QR movement, Ohio has flourishing secondary and postsecondary QR courses, which we describe.References
Adabor, J. K., & Foley, G. D. (2010). Maximizing the area of a sector with fixed perimeter. Ohio Journal of School Mathematics, 62, 17–23.
Adabor, J. K., & Foley, G. D. (2013). Shape affects the sound of a drum: Modeling area and perimeter. Ohio Journal of School Mathematics, 68, 1–6.
Alhammouri, A. M., & Foley, G. D. (2019). Developing financial literacy and mathematical prowess by modeling using spreadsheets. MathAMATYC Educator, 10(3), 23–34, 65–66.
Alhammouri, A. M., Foley, G. D., & Dael, K. (2018). Tracking trout: Engaging students in modeling. Mathematics Teacher, 111, 416–423.
Alhammouri, A., Durkee, J., & Foley, G. D. (2017). Where to place a post? Engaging students in the mathematical modeling process. Ohio Journal of School Mathematics, 75, 42–49.
American Statistical Association. (2016). Guidelines for assessment and instruction in statistics education (GAISE) college report 2016. Everson, M. (Cochair), Mocko, M. (Cochair), Carver, R., Gabrosek, J., Horton, N., Lock, R., Rossman, A., Rowell, G. H., Velleman, P, Witmer, J., & Wood, B. Alexandria, VA: American Statistical Association. http://www.amstat.org/education/gaise/ GaiseCollege_Full.pdf
Celebrating 20 years of the AP Statistics exam. (2017, November 1). Amstat News. https://magazine.amstat.org/blog/2017/11/01/ap-statistics-exam/
Committee on the Undergraduate Program in Mathematics (CUPM). (2004).
Undergraduate programs and courses in the mathematical sciences: CUPM curriculum guide 2004. Mathematical Association of America. https://www.maa.org/sites/default/files/pdf/CUPM/cupm2004.pdf
Dana Center, Charles A., University of Texas at Austin. (2020, March). Launch years: A new vision for the transition from high school to postsecondary mathematics. https://utdanacenter.org/launchyears
Elrod, S. (2014). Quantitative reasoning: The next “across the curriculum
Foley, G. D., Butts, T. R., Phelps, S. W., & Showalter, D. A. (2017). Advanced quantitative reasoning: Mathematics for the world around us. (rev. ed.). AQR Press.
Leitzel, Joan R. (Chair). (2014, March). Rethinking postsecondary mathematics: Final report of the Ohio Mathematics Steering Committee. Ohio Department of Higher Education. https://dcmathpathways.org/sites/default/files/2016-08/Rethinking%20Postsecondary%20Mathematics_%20Final%20report%20of%20the%20Ohio%20Mathematics%20Steering%20Committee.pdf
Madison, B. L. (2019). Quantitative literacy: An orphan no longer. In S. L. Tunstall, G. Karaali, & V. Piercey (Eds.), Shifting contexts, stable core: Advancing quantitative literacy in higher education (pp. 37–46). Mathematical Association of America.
Mayes, R. L., Forrester, J., Schuttlefield Christus, J., Peterson, F., & Walker, R. (2014). Quantitative reasoning learning progression: The matrix. Numeracy: Advancing Education in Quantitative Literacy, 7(2), Article 5. http://dx.doi.org/10.5038/1936-4660.7.2.5
National Council of Teachers of Mathematics & American Statistical Association. (2020). Pre-K–12 guidelines for assessment and instruction in statistics education (GAISE II): A framework for statistics and data science education. (Writing Committee: Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., & Spangler, D. A.) American Statistical Association. https://www.amstat.org/asa/files/pdfs/GAISE/GAISEIIPreK-12_Full.pdf
National Research Council. (2001). Knowing what students know: The science and design of educational assessment.
Pelligrino, J. W., Chudowsky, N., & Glaser, R. (Eds.). Committee on Foundations of Assessment, Board on Testing and Assessment, Center for Education, Division of Behavioral and Social Sciences and Education. National Academy Press.
Ohio Department of Education. (2018). Algebra 2 and Mathematics 3 course standards. http://education.ohio.gov/getattachment/Topics/Learning-in-Ohio/Mathematics/Ohio-s-Learning-Standards-in-Mathematics/ALGEBRA-2-MATH-3-Standards.pdf.aspx?lang=en-US
Ohio Department of Higher Education. (2015, December). TMM011—Quantitative Reasoning. https://www.ohiohighered.org/sites/ohiohighered.org/files/uploads/transfer/documents/OTM/TMM011%20Quantitative%20Reasoning%20FINALIZED%20v2-%2012-21-2015.pdf
Ohio Department of Higher Education. (2016, April). TMM001—College Algebra. https://www.ohiohighered.org/sites/ohiohighered.org/files/uploads/transfer/documents/OTM/TMM001%20College%20Algebra%20Revised%20Learning%20Outcomes%20-%20Updated%20Sample%20Tasks%204-30-2016.pdf
Pollak, H. O. (1966). On individual exploration in mathematics education. In E. G. Begle (Ed.), The role of axiomatics and problem solving in mathematics (pp. 117–122). Conference Board of the Mathematical Sciences (published by Ginn)
Pólya, G. (1957). How to solve it: A new aspect of mathematical method (2nd ed.). Princeton University Press. (Reprinted in paperback 1971; copyright renewed 1973)
Stein, M. K., Grover, B. W., & Henningsen, M. (1996). Building student capacity for mathematical thinking and reasoning: An analysis of mathematical tasks used in reform classrooms. American Educational Research Journal, 33, 455–488.
Stein, M. K., Smith, M. S., Henningsen, M. A., & Silver, E. A. (2009). Implementing standards-based mathematics instruction: A casebook for professional development (2nd ed.). National Council of Teachers of Mathematics & Teachers College Press.
Strayer, J. F., & Edwards, M. T. (2015). Smarter cookies: An inquiry-based project to examine statistical claims encourages students to become more savvy media consumers. Mathematics Teacher, 108, 608–615.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Gregory D. Foley, Patrick W. Wachira
