LAUSR

Cornerstone design courses have become a major part of engineering curricula, where students with different personality types and learning styles work together to design, develop, build, and demonstrate the functionality of a prototype within the duration of a term. This study analyzes student and team performance against gender, personality types, and learning styles in a second-year engineering design course. Further, the correlations between several assessment mechanisms are studied, and the effects of three different instructional design approaches on students’ performance are explored. Data have been collected on student performance and psychometrics, including marks, gender, personality type, and learning style from 2001 to 2018. To identify students’ personality types and learning styles, Myers–Briggs Type Indicators (MBTI) and Neil Fleming’s Learning VARK tests were administered. To evaluate students’ performance in the course, a number of assessment mechanisms have been defined. Several statistical methods are used to analyze data, and to determine correlation between datasets. Over nearly two decades of marks, gender, MBTI, and VARK data for 2637 students are presented for an engineering design course. The results demonstrated that there was no significant difference in performance across most assessments based on gender or gender distribution on a team. A better performance was observed from VK bimodal and quadmodal learning styles in most assessment mechanisms. Further, certain MBTI groups, namely, judging types outperformed their peers in engineering design assessments, with interesting interplay between MBTI dimensions for specific assessments and team dynamics. Traditional assessment mechanisms, such as engineering notebook and design proposals, are shown to be good predictors of student success. Lastly, scaffolded design activities and front-loading of lecture content were shown to be beneficial for student learning. There is negligible performance difference between female and male students in the engineering design course. Students whose preferred learning styles align with the assessment themes showed better performance in the course. The outcomes of this paper can be readily applied by instructors for design of assessment mechanisms, course materials, team formation, and instructional design.