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Students of Computer Science often wonder when, exactly, one can apply agreedy algorithm to a problem, and when one must use the more complicated andtime-consuming techniques of dynamic programming. This paper argues that theexisting pedagogical literature does not offer clear guidance on this issue. Wesuggest improving computer science pedagogy by importing a concept economistsuse in their own implementations of dynamic programming. That economic conceptis "opportunity cost," and we explain how it can aid students indifferentiating "greedy problems" from problems requiring dynamic programming

Illustrating the Suitability of Greedy and Dynamic Algorithms Using The Economics Concept of "Opportunity Cost"