Shira Viel, Ph.D.

Adjunct Associate Professor

Milwaukee WI UNITED STATES

Dr. Viel has ten years of experience teaching undergraduate math.

Contact

Education, Licensure and Certification

Ph.D.

Mathematics

North Carolina State University

2018

M.S.

Mathematics and Theatre

North Carolina State University

2014

B.A.

Mathematics

Rice University

2009

Biography

Shira Viel, Ph.D., is an Adjunct Associate Professor at Milwaukee School of Engineering. Her professional work focuses on mathematics education, undergraduate instruction and mathematical research.

Her education research examines classroom community, student belonging, inclusive assessment and the design of introductory mathematics courses. Her work addresses how course structures and teaching practices influence undergraduate students' experiences in mathematics and statistics.

Viel has also contributed to research in algebraic and geometric combinatorics, including work on cluster algebras, generalized splines on graphs, geometric coefficients and algebraic voting theory. Her teaching and curriculum interests include calculus, discrete mathematics and quantitative learning.

She earned a Ph.D. in mathematics from North Carolina State University and has held teaching and research roles in higher education. Her professional activities have included mathematics outreach, faculty development, curriculum design and participation in organizations including the Mathematical Association of America, the Special Interest Group on Research in Undergraduate Mathematics Education and the Association for Women in Mathematics.

Areas of Expertise

STEM Student Success‎

Mathematics Research

Mathematics Education

Curriculum Development

Inclusive Assessment‎

Affiliations

Mathematical Association of America (MAA)
Special Interest Group on Research in Undergraduate Mathematics Education (SIGMAA on RUME)
Association for Women in Mathematics (AWM)

Social

Event and Speaking Appearances

Classroom Community in Introductory Undergraduate Mathematics and Statistics: A Mixed Methods Study of Student Belonging and Course Attributes

International Conference on Learning Utrecht, Netherlands

2024-07-11

Self-reported Student Motivations to Participate in DEI Service Work

Conference on Research in Undergraduate Mathematics Education

2024-02-22

Inclusive Assessment in Quantitative Courses

Duke Learning Innovation Faculty Learning Community Panel

2022-09-19

Selected Publications

A Mixed-Methods Study of Classroom Community Among Undergraduate Students in Introductory Mathematics and Statistics

The International Journal of Learner Diversity and Identities

Shira Viel, Maria A. Tackett, Sarwari Das, Joseph Choo

2025-01-01

A strong sense of classroom community is associated with many positive learning outcomes and is a crucial contributor to undergraduate students’ persistence in STEM, particularly for women and students of color. This article describes a mixed-methods investigation into the relationship between classroom community and course attributes in introductory undergraduate mathematics and statistics courses, mediated by student identities.

Utilizing a Blended + Flipped Learning Approach in a Calculus for Life and Management Sciences Classroom

PRIMUS

Dan Spencer, Chris Willis, Yan Shen, Molly Fenn, Shira Viel

2022-11-03

The current study evaluated the success of implementing a blended + flipped structure in a Calculus for Life and Management Sciences course. By reimagining two of the three weekly instructional hours as online asynchronous lessons, we redesigned a 200-person section into 30-person sections, with minimal additional instructor resources. Findings indicated that students viewed the course positively, with perceptions positively correlating with course outcomes. Further, students reported more positive beliefs relating to their ability to accomplish course learning outcomes, comfort with math, and perceptions of in-class readiness compared to those in the traditional course format. Significant differences in grade distributions were also observed.

Algebraic voting theory & representations of S≀S

Advances in Applied Mathematics

Hélène Barcelo, Megan Bernstein, Sarah Bockting-Conrad, Erin McNicholas, Kathryn Nyman, Shira Viel

2020-07-03

We consider the problem of selecting an n-member committee made up of one of m candidates from each of n distinct departments. Using an algebraic approach, we analyze positional voting procedures, including the Borda count, as QSm≀Sn-module homomorphisms. In particular, we decompose the spaces of voter preferences and election results into simple QSm≀Sn-submodules and apply Schur's Lemma to determine the structure of the information lost in the voting process. We conclude with a voting paradox result, showing that for sufficiently different weighting vectors, applying the associated positional voting procedures to the same set of votes can yield vastly different election outcomes.