Numerical Problem Solving across the Curriculum with Python and MATLAB Using Interactive Coding Templates: A Workshop for Chemical Engineering Faculty

Austin N. Johns; Robert P. Hesketh; Matthew D. Stuber; Ashlee N. Ford Versypt

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: Chemical Engineering Division (ChED) Technical Session 7: Innovative Pedagogy
Tagged Division: Chemical Engineering Division (ChED)
Page Count: 22
DOI: 10.18260/1-2--43749
Permanent URL: https://peer.asee.org/43749
Download Count: 294

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Paper Authors

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Austin N. Johns The State University of New York, Buffalo

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Austin N. Johns is an active-duty captain and developmental engineer in the United States Air Force. In 2017, he earned a B.S. in Chemical Engineering from Oklahoma State University. In 2023, he earned a M.S. in Chemical Engineering from the University at Buffalo, The State University of New York. His graduate research focused on developing computational educational resources for use in the chemical engineering curriculum. The views expressed in this paper are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U.S. Government.

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Robert P. Hesketh Rowan University

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Robert Hesketh is a Professor of Chemical Engineering at Rowan University. He received his B.S. in 1982 from the University of Illinois and his Ph.D. from the University of Delaware in 1987. After his Ph.D. he conducted research at the University of Cam

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Matthew D. Stuber University of Connecticut

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Dr. Matt Stuber is an Assistant Professor with the Dept. of Chemical & Biomolecular Engineering and the Institute for Advanced Systems Engineering at the University of Connecticut. He received his PhD from the Massachusetts Institute of Technology (MIT) and his BS from the University of Minnesota – Twin cities, both in chemical engineering. In his post-doctoral work, he cofounded a water-tech start-up company focusing on developing flexible high-efficiency solar-driven desalination technologies for diverse applications where membrane technologies prove inadequate. At UConn, his core research focus is on optimization theory, methods, and software for modeling and simulation, robust simulation and design, and controls and operations. His application interests lie in addressing challenging and timely applications from a spectrum of industries including food, energy, water and natural resources, chemicals, finance, and healthcare. The systems-level thinking combined with quantitative rigor enables the development of novel solutions to emerging and intractable problems across these diverse areas.

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Ashlee N. Ford Versypt The State University of New York, Buffalo orcid.org/0000-0001-9059-5703

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Dr. Ashlee N. Ford Versypt is an Associate Professor in the Department of Chemical and Biological Engineering at the University at Buffalo (UB), The State University of New York. She is also an Affiliated Faculty in the Department of Engineering Education and the Institute for Artificial Intelligence and Data Science. She received her B.S. from the University of Oklahoma and her M.S. and Ph.D. from the University of Illinois. She did a postdoc at the Massachusetts Institute of Technology before starting her academic career at Oklahoma State University (OSU), where she was an assistant professor 2014-2020 and then a tenured associate professor until January 2021 before moving to UB. Dr. Ford Versypt leads the Systems Biomedicine and Pharmaceutics Laboratory. She was the 2020-2021 Chair for the ASEE Chemical Engineering Division (CHED). Dr. Ford Versypt has been recognized with the NSF CAREER Award, ASEE CHED Ray W. Fahien Award and Joseph J. Martin Award, and AIChE CAST Division David Himmelblau Award for Innovations in Computer-Based Chemical Engineering Education. She is an Academic Trustee of Computer Aids for Chemical Engineering Corporation.

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Abstract

With the fourth industrial revolution well underway, the proportion of occupations requiring “high” or “medium” digital skills has never been greater. Among those most in demand are engineers skilled in computing and advanced problem solving to support the ongoing digitalization, networking, and automation. A numerical analysis course in the core undergraduate engineering curriculum is a natural place for students to learn numerical methods for advanced problem solving across engineering applications. The use of computing across the entire chemical engineering curriculum also offers opportunities to hone students’ abilities as computational thinkers and effective problem solvers to meet the current and future needs of an increasingly complex and digital industry and society. While the current chemical engineering curriculum includes computational training, there is a need to efficiently increase the exposure of students to computing within mathematical problem-solving contexts and develop their proficiency in computer programming, all while balancing demands to reduce credit hours. Some chemical engineering faculty interested in enhancing the computational nature of their courses face a barrier to doing so due to unfamiliarity with some modern computational educational resources that may not have been covered in their training or may not be used in their research areas. The authors developed a workshop to teach chemical engineering faculty to use and develop interactive coding templates (MATLAB Live Scripts and Jupyter Notebooks) and to equip faculty to incorporate these techniques across the undergraduate curriculum. The workshop was presented at the 2022 ASEE/AIChE Summer School for Engineering Faculty. The purpose of this paper is to disseminate the workshop resources, providing educators with a suite of interactive templates focused on chemical engineering-related case studies and with training to create and adapt their own related materials. The paper details the interactive coding templates provided during the workshop along with the relevant pedagogical background and some lessons learned for future related workshops. Educators who did not attend the workshop are also a target audience of this paper as it provides tips and access to the relevant materials for implementing computational thinking through interactive coding templates into their classroom practices.

Citation
Format

Johns, A. N., & Hesketh, R. P., & Stuber, M. D., & Ford Versypt, A. N. (2023, June), Numerical Problem Solving across the Curriculum with Python and MATLAB Using Interactive Coding Templates: A Workshop for Chemical Engineering Faculty Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43749

TY - CPAPER
AB - With the fourth industrial revolution well underway, the proportion of occupations requiring “high” or “medium” digital skills has never been greater. Among those most in demand are engineers skilled in computing and advanced problem solving to support the ongoing digitalization, networking, and automation. A numerical analysis course in the core undergraduate engineering curriculum is a natural place for students to learn numerical methods for advanced problem solving across engineering applications. The use of computing across the entire chemical engineering curriculum also offers opportunities to hone students’ abilities as computational thinkers and effective problem solvers to meet the current and future needs of an increasingly complex and digital industry and society. While the current chemical engineering curriculum includes computational training, there is a need to efficiently increase the exposure of students to computing within mathematical problem-solving contexts and develop their proficiency in computer programming, all while balancing demands to reduce credit hours. Some chemical engineering faculty interested in enhancing the computational nature of their courses face a barrier to doing so due to unfamiliarity with some modern computational educational resources that may not have been covered in their training or may not be used in their research areas. The authors developed a workshop to teach chemical engineering faculty to use and develop interactive coding templates (MATLAB Live Scripts and Jupyter Notebooks) and to equip faculty to incorporate these techniques across the undergraduate curriculum. The workshop was presented at the 2022 ASEE/AIChE Summer School for Engineering Faculty. The purpose of this paper is to disseminate the workshop resources, providing educators with a suite of interactive templates focused on chemical engineering-related case studies and with training to create and adapt their own related materials. The paper details the interactive coding templates provided during the workshop along with the relevant pedagogical background and some lessons learned for future related workshops. Educators who did not attend the workshop are also a target audience of this paper as it provides tips and access to the relevant materials for implementing computational thinking through interactive coding templates into their classroom practices.
AU - Austin N. Johns
AU - Robert P. Hesketh
AU - Matthew D. Stuber
AU - Ashlee N. Ford Versypt
CY - Baltimore , Maryland
DA - 2023/06/25
PB - ASEE Conferences
TI - Numerical Problem Solving across the Curriculum with Python and MATLAB Using Interactive Coding Templates: A Workshop for Chemical Engineering Faculty
UR - https://peer.asee.org/43749
DO - 10.18260/1-2--43749
ER -