Cool Class: Industrial Mathematics

May 03, 2022

By J. Charlotte Jarrett ’08

Students in an independent study math course meet to collaborate on research.
Photo by Scott Cook.

Students in this independent study course experienced firsthand one of the many practical career applications of a math degree: working together to analyze data and find innovative solutions for real problems.

Supported by a grant from the MAA Preparation for Industrial Careers in Mathematical Sciences (PIC Math), seven math majors put the knowledge, creativity, and problem-solving skills they’ve been honing in the classroom to work in the real world. In partnership with Ohio-based research firm Broadview Analytics, students in this independent study course analyzed data collected from college and university professors to yield tangible results regarding textbook evaluation.

Math professor Zeynep Teymuroglu, who secured the grant funding, went through an intensive MAA PIC faculty training prior to the independent study, working with experts in industrial mathematics and searching out a real-life problem for the class to tackle. Aside from supporting the momentous solutions to come, the grant also provided class participants with travel funding to present their work at an upcoming national math conference.

“The opportunity to work with Rollins has provided benefits for both Broadview Analytics and Rollins students,” says the research firm’s president, Joseph Stephan. “Broadview gets to see how the newest generation processes information and uses modern tools in their workflow while the students get exposure to real-world challenges that lie at the heart of applied mathematics.”

And in this case, it doesn’t take a math expert to see the partnership is a win-win. Ultimately, the classmates pooled their mathematical prowess and delivered actionable insights for Broadview—just like they will as powerfully equipped Rollins graduates as they take their next steps in the workforce.

Instructor & Industry Partner

  • Zeynep Teymuroglu, associate professor of mathematics
  • Broadview Analytics, research and analytical services firm
Students in an independent study math course meet to collaborate on research.
Photo by Scott Cook.

The Scoop

“This course was designed to provide students a hybrid experience, merging an internship and a research project,” explains Teymuroglu. “It’s a high-impact teaching and learning practice that provides a platform for students to apply their in-class knowledge to a real-world problem.”

The semester-long research issue came directly from Broadview Analytics, as the class was asked to analyze a large data set of textbook attributes such as math rigor, coverage, and conceptual understanding, and conclude which characteristics make math textbooks most desirable for a specified class. The independent study provided a unique opportunity for the students, who expanded their career views exponentially over the course of the term.

“Most of our students are double majors in economics, business management, or international business,” says Teymuroglu. “This project gave them an opportunity to bring their knowledge about market research, statistics, and econometrics to the table and gain hands-on experience in the process.”

Students in an independent study math course meet to collaborate on research.
Photo by Scott Cook.


We dropped in on the class during one of their final research sessions as Teymuroglu and the students were collaborating to assess and analyze the data collected from more than 300 professors at different colleges and universities.

Throughout the semester, the team used principal component analysis to reduce the dimensionality of the data set and were ultimately able to report to the client that all attributes can be grouped into three major categories: mathematical thinking, problem solving skills, and content coverage.

These findings can now be used to rank mathematical textbooks based on the needs of professors and better serve future students, bringing the powerful learning opportunity full circle.

Students collaborate on a research project for their Industrial Math independent study course.
Photo by Scott Cook.

Student Perspective

“This experience really opened my mind to what you can do with a math degree,” says economics and math double major Jurel Mua ’23. “After doing this research and talking with our collaborators, we realized that math lays the foundation for almost everything you want to do, be it business or psychology. If you understand the data, you get everything.”

Math major Adriane Griffith ’22, who conducted student-faculty research last summer with Teymuroglu on the effect of Rollins’ COVID-19 cases on the surrounding community—found this research project crucial to her development in her major.

“This experience has helped hone my ability to communicate math data, which will benefit me in any STEM career field that I enter,” she says.

Exploration, freedom, creativity, and communication were common themes among the students as they reflected on this process and saw the power of mathematics come to life.

“My biggest takeaway from the class is the opportunity to let my imagination run wild,” says Sara Sarwat Casanova ’23, a double major in math and international business. “There wasn’t a specific solution we had to find—instead we were given one question and had to work as a team to reach the best possible solution for the client. I didn’t feel like we were following the teacher’s instructions but rather were all working collaboratively to achieve the same objective, and that’s what real life is about.”

Math professor Zeynep Teymuroglu works alongside her independent study students on a research project.
Photo by Scott Cook.

Did You Know?

Teymuroglu has secured another grant sponsored by the Center of Undergraduate Research in Mathematics. With this funding, a different group of students will study the spread of the opioid crisis and innovate real-life solutions.

PIC Math is a program of the Mathematical Association of America (MAA) and the Society for Industrial and Applied Mathematics (SIAM). Support is provided by the National Science Foundation (NSF grant DMS-1722275).

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