Overcoming Non-numerical Challenges in an Engineering Numerical Methods Course

Ivan Detchev; Elena Rangelova; Sheng Lun (Christine) Cao

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Conference: 2020 ASEE Virtual Annual Conference Content Access
Location: Virtual On line
Publication Date: June 22, 2020
Start Date: June 22, 2020
End Date: June 26, 2021
Conference Session: New Engineering Educators 4: Tips and Tools
Tagged Division: New Engineering Educators
Page Count: 15
DOI: 10.18260/1-2--35025
Permanent URL: https://strategy.asee.org/35025
Download Count: 459

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Paper Authors

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Ivan Detchev University of Calgary

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Ivan Detchev holds a BScE (first division) from the department of Geodesy and Geomatics Engineering at the University of New Brunswick. He also obtained a MSc and a PhD in Geomatics Engineering from the University of Calgary. Dr. Detchev is currently an instructor in surveying and mapping at the University of Calgary. He is interested in the scholarship of teaching and learning (SoTL) related to engineering education.

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Elena Rangelova University of Calgary

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Dr. Elena Rangelova is a senior instructor in the Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary. She received her PhD degree from the same department in 2007. Her research interests in scholarship of teaching and learning are in the field of deep, active and team-based learning, as well as transformative learning in threshold concepts.

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Sheng Lun (Christine) Cao University of Calgary

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Sheng Lun (Christine) Cao is a second-year Master of science student at the Schulich School of Engineering, University of Calgary. Her primary research field is in applied machine learning on urban planning and development. Due to her interest in Engineering Education, Christine also works as a research assistant for Dr. Elena Rangelova and Dr. Ivan Detchev.

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Abstract

This paper addresses the most current pedagogical practices in an engineering numerical methods course. The paper describes the course, explains its challenges, and covers the instructional remedies developed in order to improve students’ learning experience. The course instructor is a new engineering educator who would like to share his course design and get feedback on the implemented course improvements.

The numerical methods course is a common-core engineering course taken by primarily civil, mechanical, and geomatics engineering students in either their second or third year. The topics in the course include solutions to linear and non-linear equations and systems of equations, interpolation, curve fitting, numerical differentiation and integration, and ordinary differential equations. The course content is based off of a standard textbook in numerical methods which uses MATLAB as a programming language. The learning outcomes include choosing appropriate methods for solving a given engineering problem and proficiently programming the algorithms associated with the methods in MATLAB. The course normally runs as three hours of lectures and two hours of tutorials a week. The assessment items are typically five assignments, one or two midterms, and a final exam.

This course faces several challenges. One of the major issues is that the student demographic can be divided into two distinct groups – students who have no MATLAB background, and students who have experience programming in MATLAB in at least one course prior to enrolling in numerical methods. Amongst the student population, the course has the stigma of being a dry math course. Since it is a terminal course, many of the students lack the motivation of performing well in it other than for getting the grade and credit for the course. On the instructional side, the course has anecdotally been considered as a penalty when assigned as part of the teaching load. In addition, there has been an unsuccessful attempt at teaching the course in a blended manner.

The latest developments in this course have been remedies addressing the listed challenges. A pilot iteration of the course was run in a fundamentally different way. The class was divided into groups where the members of each group were meant to have a well-rounded set of skills as a whole, e.g., programming experience, interest in math, presentation skills, and technical writing skills. The old assignments were clearly separated into a set of conceptual self-assessment questions (homework assignments done individually), and programming exercises (labs primarily done in the tutorial contact hours and requiring group reports). The course also included a student-lead/inquiry-based final project (group oral presentation and technical report) in order to inspire the applicability of the learned material. Finally, the lecture contact hours were meant to include multiple active learning strategies, such as team-based learning inspired quizzes, solving example problems, and performing MATLAB demos in class. The paper will also include a third-party evaluation of some of the developments, where a research assistant conducted several in-class observations, lesson minute papers, and end-of-unit surveys.

Citation
Format

Detchev, I., & Rangelova, E., & Cao, S. L. C. (2020, June), Overcoming Non-numerical Challenges in an Engineering Numerical Methods Course Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35025

TY - CPAPER
AB - This paper addresses the most current pedagogical practices in an engineering numerical methods course. The paper describes the course, explains its challenges, and covers the instructional remedies developed in order to improve students’ learning experience. The course instructor is a new engineering educator who would like to share his course design and get feedback on the implemented course improvements.

The numerical methods course is a common-core engineering course taken by primarily civil, mechanical, and geomatics engineering students in either their second or third year. The topics in the course include solutions to linear and non-linear equations and systems of equations, interpolation, curve fitting, numerical differentiation and integration, and ordinary differential equations. The course content is based off of a standard textbook in numerical methods which uses MATLAB as a programming language. The learning outcomes include choosing appropriate methods for solving a given engineering problem and proficiently programming the algorithms associated with the methods in MATLAB. The course normally runs as three hours of lectures and two hours of tutorials a week. The assessment items are typically five assignments, one or two midterms, and a final exam.

This course faces several challenges. One of the major issues is that the student demographic can be divided into two distinct groups – students who have no MATLAB background, and students who have experience programming in MATLAB in at least one course prior to enrolling in numerical methods. Amongst the student population, the course has the stigma of being a dry math course. Since it is a terminal course, many of the students lack the motivation of performing well in it other than for getting the grade and credit for the course. On the instructional side, the course has anecdotally been considered as a penalty when assigned as part of the teaching load. In addition, there has been an unsuccessful attempt at teaching the course in a blended manner.

The latest developments in this course have been remedies addressing the listed challenges. A pilot iteration of the course was run in a fundamentally different way. The class was divided into groups where the members of each group were meant to have a well-rounded set of skills as a whole, e.g., programming experience, interest in math, presentation skills, and technical writing skills. The old assignments were clearly separated into a set of conceptual self-assessment questions (homework assignments done individually), and programming exercises (labs primarily done in the tutorial contact hours and requiring group reports). The course also included a student-lead/inquiry-based final project (group oral presentation and technical report) in order to inspire the applicability of the learned material. Finally, the lecture contact hours were meant to include multiple active learning strategies, such as team-based learning inspired quizzes, solving example problems, and performing MATLAB demos in class. The paper will also include a third-party evaluation of some of the developments, where a research assistant conducted several in-class observations, lesson minute papers, and end-of-unit surveys.
AU - Ivan Detchev
AU - Elena Rangelova
AU - Sheng Lun (Christine) Cao
CY - Virtual On line
DA - 2020/06/22
PB - ASEE Conferences
TI - Overcoming Non-numerical Challenges in an Engineering Numerical Methods Course
UR - https://strategy.asee.org/35025
DO - 10.18260/1-2--35025
ER -