Student NameTeegan Bailey
Faculty Mentor NameDarryl, Chamberlain Jr., PhD
CollegeCollege of Liberal Arts and Sciences
Research InterestsMathematics, Mathematics Education
Academic AwardsPresidents Honor Roll, Emerging Scholars Program 2021
OrganizationsPreview Staff, University Math Society, Bridges Minority Scholars Outreach Program, Florida Club Swim and Dive
Hobbies and InterestsPhotography, Programming, Cooking, Coffee

Research Project

Undergraduate’s Covariational Reasoning with Parametric Representations

Covariational Reasoning is the reasoning ability students use to understand and interpret how distinct quantities vary with respect to one another. Covariational reasoning itself is an underlying concept throughout mathematics, especially in higher-level courses. Measuring students’ covariational reasoning gives a better understanding of how students interact with increasingly complex mathematical concepts, which in turn can be used to better prepare students for success in future mathematics courses. This study will investigate how Calculus 1 students are able to apply two different types of covariational reasoning to linear and nonlinear functions: simultaneously-independent reasoning and change-dependent reasoning. These focus on how students reason about two quantities changing in response to a third quantity and how a quantity changes in direct relation to another quantity, respectively. One area where covariational reasoning plays a significant roll in understanding how students learn is parametric representations. Students normally first encounter parametric representations after Calculus 1, where they learn to reason with multiple variables. Due to this, my research will focus on representations using linear and trigonometric representations, which is one of the first parametric representations that students are exposed to in their courses.