Upcoming Presentations

Home / Upcoming Presentations

How Does Video Analysis Influcence Pre-Service Teachers’ Ability to Notice Student Mathematical Thinking While Teaching?

Presenters: Dawn Teuscher, Brigham Young University and J. Matt Switzer, Texas Christian University
Location: AMTE 2018 in Houston, Texas
We share findings from an analysis of eight pre-service secondary mathematics teachers’ ability to notice student mathematical thinking while student teaching and discuss differences among student teachers who had varying degrees of exposure to analyzing video during their undergraduate program.

Teachers’ Orientations around Using Student Mathematical Thinking as a Resource during Whole-class discussion

Presenters: Keith Leatham, Brigham Young University; Blake Peterson, Brigham Young University; Shari Stockero, Michigan Technological University; Mary Ochieng, Western Michigan University; and Laura Van Zoest, Western Michigan University.
Location: AMTE 2018 Conference in Houston, Texas
We characterize teachers’ orientations related to using student mathematical thinking as a resource during whole-class discussion. We consider the potential these orientations provide to either support or hinder the development of the practice of building on student mathematical thinking.

Students’ Strategies for Setting up Differential Equations in Engineering Contexts

Presenters: Steven Jones and Omar Naranjo, Brigham Young University
Location: RUME Conference, San Diego, California
Ordinary differential equations (ODEs) comprise an important tool for mathematical modelling in science and engineering. This study focuses on how students in an engineering system dynamics course organized the act of setting up ODEs for complex engineering contexts. Through the lens of ODEs as a “coordination class” concept, we examined the strategies that seemed to guide the students’ interpretations of problem tasks and their activation of knowledge elements during the tasks, as the students worked to produce ODEs for those tasks. This led to our uncovering of three main strategies guiding the students’ work, and the finding that being able to flexibly draw on all of these strategies may be beneficial for student success.

Students’ Usage of Visual Imagery to Reason about the Divergence, Integral, Direct Comparison, Limit Comparison, Ratio, and Root Convergence Tests

Presenters: Steven Jones and Mitchell Probst, Brigham Young University
Location: RUME Conference, San Diego, California
This study was motivated by practical issues we have encountered as second-semester calculus instructors, where students struggle to make sense of the various series convergence tests, including the divergence, integral, direct comparison, limit comparison, ratio, and root tests. To begin an exploration of how students might reason about these tests, we examined the visual imagery used by students when asked to describe what these tests are and why they provide the conclusions they do. It appeared that each test had certain types of visual imagery associated with it, which were at times productive and at times a hindrance. We describe how the visual imagery used by students seemed to impact their reasoning about the convergence tests.

Building on Covariation: Making Explicit Four Types of “Multivariation”

Presenters: Steven Jones, Brigham Young University
Location: RUME Conference, San Diego, California
Covariation and covariational reasoning have become key themes in mathematics education research. In this theoretical paper, I build on the construct of covariation by considering cases where more than two variables relate to each other, in what can be called “multivariation.” I share the results of a conceptual analysis that led to the identification of four distinct types of multivariation: independent, dependent, nested, and vector. I also describe a second conceptual analysis in which I took the mental actions of relationship, increase/decrease, and amount from the covariational reasoning framework, and imagined what analogous mental actions might be for each of these types of multivariation. These conceptual analyses are useful in order to scaffold future empirical work in creating a complete multivariational reasoning framework.

A Study of Calculus Students’ Solution Strategies when Solving Related Rates of Change Problems

Presenters: Steven Jones, Brigham Young University and Peter Thembinkosi, Miami University of Ohio
Location: RUME Conference, San Diego, California
Contributing to the growing body of research on students’ understanding of related rates of change problems, this study reports on the analysis of solution strategies used by five calculus students when solving three related rates of change problems where the underlying independent variable in each problem was time. Contrary to findings of previous research on students’ understanding of related rate of change problems, all the students in this study were able to translate prose to algebraic symbols. All the students had a common benchmark to guide their overall work in one of the tasks but no benchmark to guide their overall work in the other two tasks. Three students exhibited weaker calculational knowledge of the product rule of differentiation. Directions for future research and implications for instruction are included.

CPR for the Common Core: Using the Comprehensive Mathematics Instruction (CMI) Framework to Unpack Standards Across a Learning Cycle

Presenters: Scott Hendrickson and Sterling Hilton, Brigham Young University
Location: NCSM Conference, Washington DC
The Comprehensive Mathematics Instruction (CMI) Framework developed by the Brigham Young University Public School Partnership informs teachers on how to align CCSSM content standards along a progression from emerging ideas, strategies and representations towards more robust conceptual, procedural, and representational understanding. In this session participants will use the CMI framework to deepen their understanding of a subset of high school standards as they select, sequence and connect these standards across a learning cycle of instruction.