Comparing Outcomes Between Two Engineering Majors in a Deterministic Operations Research Course

In an introductory undergraduate-level deterministic modeling course that covers linear and integer programming, students apply modeling and optimization approaches to address challenges related to network flows, project management, transportation, and assignment problems. They also acquire proficiency in various solution strategies, including the simplex method and the branch- and-bound approach. Duality and sensitivity analysis are comprehensively covered, as well as their economic interpretations. Both Industrial Engineering and Mechanical Engineering students share access to identical learning modules, completing the same assignments and exams. The objective of this study is to compare the performance of these two student cohorts and assess their abilities in three crucial areas: proficiency in matrix algebra, the capacity to identify and formulate engineering problems, and the ability to solve and interpret these problems. The study's findings reveal that Mechanical Engineering students outperformed their counterparts overall. This group demonstrated stronger skills in comprehensively understanding the problem scope and formulating problems into mathematical models. Additionally, the study underscores the significance of applied examples, serving as a crucial bridge connecting theoretical understanding with practical application. This pedagogical approach fosters a deeper comprehension of the subject matter, proving beneficial for students across various engineering disciplines.