Sensitivity analysis, a key linear programming (LP) concept, is often explained in text books using complex problem scenarios that students have difficulty relating to. Consequently, many students do not fully comprehend nor appreciate significance of shadow prices or range of optimality for objective coefficients. This adds to the challenges instructors face in promoting critical thinking, a key goal in operations research and management science courses. Limited student-faculty interactions further exacerbates the problem in online learning environments. These issues can be effectively addressed through use of simple real world examples for instruction, followed by discussion of insights and intuition behind results from these mathematical models. This forms the motivation of this study, with a special focus on sensitivity analysis concepts and LP formulations. We then demonstrate its effectiveness by comparing student performance before and after exposure to this innovative teaching supplement and as well as results from a student feedback survey.