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An Interdisciplinary Elective Course to Build Computational Skills for Mathematical Modeling in Science and Engineering

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Conference

2019 ASEE Annual Conference & Exposition

Location

Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

June 19, 2019

Conference Session

Computer-Based Learning in Chemical Engineering Courses

Tagged Division

Chemical Engineering

Page Count

13

Permanent URL

https://peer.asee.org/32072

Download Count

8

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Paper Authors

biography

Ashlee N. Ford Versypt Oklahoma State University

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Dr. Ashlee N. Ford Versypt is an assistant professor in the School of Chemical Engineering at Oklahoma State University. She earned her Ph.D. and M.S. degrees in ChE at the University of Illinois at Urbana-Champaign and her B.S. at the University of Oklahoma. She did postdoctoral research at the Massachusetts Institute of Technology. Her research focuses on developing computational models for multiscale tissue physiology and pharmacology. Her teaching interests focus on chemical reaction kinetics and computational science and engineering. She received an NSF CAREER Award in 2019.

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Abstract

A cross-listed upper division and graduate elective course for students in science, technology, engineering, and mathematics (STEM) fields has been developed to build computational skills in mathematical modeling. The course aims to fills a gap in the practical training of students starting computational research projects across various STEM disciplines who have inconsistent previous experiences in computer programming and numerical methods. This is achieved by covering modern software tools for mathematical modeling in science and engineering and for reproducible research computing via an active, hands-on approach supplemented by reading materials. Rather than covering just the basics of programming or detailed algorithms for numerical methods, the course is geared towards implementing tools for solving realistic continuum scale science and engineering problems, managing open source code projects, and disseminating computational research results through scientific documentation and publications. The course is taught by a chemical engineering faculty member with research expertise in applied mathematics and computational science and engineering. MATLAB and Python are taught side-by-side throughout the course. The paper describes the course with the goal of enabling other educators to adapt and reuse the course content.

Ford Versypt, A. N. (2019, June), An Interdisciplinary Elective Course to Build Computational Skills for Mathematical Modeling in Science and Engineering Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. https://peer.asee.org/32072

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