Math-Stat modeling Across the Curriculum: Mid-project report

John Sieben
Professor of Math and Computer Science
Texas Lutheran University

There is a critical gap in undergraduate math education among non-STEM majors. College graduates take required math and statistics courses but don’t see the relevance of mathematical and statistical modeling to their field of study. To raise awareness of quantitative applications across disciplines, in 2019 Texas Lutheran university proposed and awarded a grant from The National Science Foundation( NSF)-IUSE program (award # 1905246 ) for a project titled “Mathematical and Statistical Projects Across the Curriculum (M2AC): Empowering Non-STEM Students to Appreciate and Use Quantitative Modeling” . This project intends to increase the use of mathematical and statistical modeling projects/modules across disciplines in non-STEM disciplines such as the social sciences, applied studies and humanities where, at the undergraduate level, the mathematical modeling is not emphasized. Modules are designed collaboratively by students and faculty from participating disciplines which involve building technology-based mathematical and statistical models and then peer reviewed and archived at: Faculty involved in this study will use these modules in their classes. We will then utilize pre- and post-instruments as well as comparison student groups to gauge impact. The main goals of the project are: 1) Increase students’ positive attitude toward the use of quantitative methods in their non-STEM courses, increase awareness of elementary quantitative applications , increase their comfort level with application of quantitative modeling and the use of technology to solve problems related to their discipline. 2) Increase among faculty outside of mathematics an appreciation for using mathematical modeling and technology to help students apply mathematical/statistical tools to their disciplines,3) Increase usage of modeling projects outside mathematics courses through project dissemination and the development of an online archive of peer-reviewed modeling projects. Building a library of peer-reviewed modeling modules is an essential part of M^2AC project. In Summer of 2020 and 2021, the PI and collaborating faculty have developed and archived over thirty discipline-specific mathematical and statistical modeling modules. Currently we are in the second year of a three-year study. In this poster presentation, we will provide a brief description of the goals of the grant, work accomplished to date, and the instruments used to measure a change in attitudes of students toward quantitative analysis after the use of these projects. We will present a sample of our modules to demonstrate the breadth of applications our colleagues from non-STEM disciplines have created. A common feature of these projects is use of real data, and commonly available technology to model current or historical events relevant to the specific disciplines.


Reza Abbasian, Texas Lutheran University, Seguin, Texas