Simulation Education; Recognising Evolving Industry Requirements and Individual Needs when Dealing with Large Class Sizes

The increasingly mainstream availability and integration of simulation tools, and the industry push towards “democratisation” places greater importance on simulation education than ever before. Many graduates will encounter simulation tools from early in their career, as perhaps the primary tool for carrying out engineering analysis on complex products. Academics have a responsibility to ensure that they understand how to use these tools confidently and reliably. However, too often competence in the domain of simulation is seen as an aptitude for using a specific software package, as opposed to a deep understanding of the underlying theory and its relation to the computational methods employed. This distinction is important in relation to university teaching; where rather than developing a course structure that is software specific, one can instead use the software to demonstrate the theoretical concepts involved in a particular discipline.
For Aerospace, Mechanical and Product Design Engineering degrees at Queen’s University Belfast, Computer-Aided Engineering (CAE) is taught as dedicated modules in Stage 3 and 4. Computer-Aided Design (CAD) is integrated to multiple design modules from Stage 1 to Stage 4 which can differ across the different subjects. Class sizes can be as high as 200 depending on individual student choices and pathways. With this number of students, there is a huge challenge associated with meeting the needs of individual students, whilst maintaining a robust assessment procedure which allows assessment of all of the learning outcomes without overburdening staff.
It will be shown in this work, how the above challenges have been addressed in course design at Queen’s. A novel approach is taken to the curriculum which recognises the industrial importance of CAD-CAE integration and subsequent validation of results. Students are challenged to consider the efficiency of the entire workflow from design through to analysis post-processing. Focus is on the underlying technologies, theory and computational methods. The students are challenged to view simulation software only as one potential route to solving a given problem, which in all instances must be substantiated. Assessment procedures are designed to challenge the students individually, whilst maintaining a common structure which enables automated marking procedures to be developed using Python and VBA scripting. A diverse range of learning resources means that students have multiple avenues of support where required.