The engineering disciplines of industrial engineering, engineering management, and systems engineering are replete with abstract concepts without physical representations that are inherently difficult to learn. Hence, this study is motivated by engineering students' inability to understand abstract concepts and the need for continuous improvement of student learning. In this study, in the context of supply chain decisions making that is economically rational, we show how we constructed and analyzed an evidence-based, in-class example of visualization aids that help engineering students to develop better understanding of abstract concepts needed in engineering problem solving. Specifically, our example was implemented in a junior level undergraduate production systems course in an industrial engineering program, which covers the areas of supply chains and logistics. To see if the visualization aids that are designed to complement the traditional approach of mathematical derivations and numerical computations, we utilize a randomized-controlled design research framework implementing the visualization aids in a quiz. Namely, an intervention group of randomly selected students were always provided with visualization aids accompanying each problem whereas a control group of randomly selected students were not. students' quiz results from both groups were statistically compared, and the statistical analyses of results show that, within the scope of the aforementioned experiment and collected data, the visualization aids help students understand abstract concepts better. The insights obtained throughout this study from the design of the visualization aids to the implementation of them in an in-class quiz will be presented. Such insights will serve as guidelines for future educational research on visualization aids towards better student learning outcomes of abstract concepts.
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