Mapping conventional teaching methods and learning styles in engineering dynamics

Abstract

Engineering dynamics is considered to be one of the most challenging courses at the University of Calgary. For the past 10 years, the failure rate has hovered around 15-20%. This rate has serious implications on student retention for the approximately 400 students each year that require engineering dynamics as prerequisite for several other core courses. An initial failure of Engineering dynamics results in a minimum of a half a year extension to a student's degree program. Furthermore, a second failure of this course requires the student to withdraw from the Engineering school. The course is offered in multiple sections, taught by several instructors using uniform teaching and assessment methods. Teaching evaluations vary across sections from very poor to those that result in teaching awards, but these results cannot be correlated with the differences in student success rate. The school assures uniformity in teaching and evaluation methods across sections. Specifically, lectures and tutorials involve theory derivations, and example problem solutions. Assignments and exams are geared toward students solving textbook type problems. Although this type of course delivery method is tried and true, and addresses most common learning styles, the student success rate for the course as a whole suggests a need for reflection. The objective of this paper is to improve student outcomes by examining the demographics and learning styles of a the Engineering Dynamics class of fall 2015. The students were surveyed to determine their learning styles using the Felder-Soloman index of learning styles (ILS) survey. The analysis shows that there are program-specific systemic barriers hindering student success. Furthermore, the learning style survey results indicate that student learning could improved by adopting a more balanced approach to teaching. Associated learning tools, specific to the dynamics curriculum, designed to address the learning outliers are suggested.