Computational problems, that is, those whose solution is given by numerical quantities, are a central theme in every field of science and technology. The present paper shows that the learning of mechanical engineering subjects where posing and solution of computational problems is important can be simplified if the structures of mathematical models, computational problems and algorithms are represented by means of dichromatic graphs. Playing the role of unusual route maps, these graphs allow the student to understand at a glance what a computational problem is, and the flow of information in the algorithms that solve the same problem. Even more important, these graphs are both guide and record of the algorithm synthesis process. The results of practical classroom experiences at graduate and undergraduate levels are given. Theoretical concepts on the paper are illustrated by means of an example taken from real-life mechanical engineering education.

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